SlideShare a Scribd company logo
1 of 79
Mathematical Induction
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
1 + 3 = 4
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
1 + 3 = 4
1 + 3 + 5 = 9
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
1 + 3 = 4
1 + 3 + 5 = 9
1 + 3 + 5 + 7 = 16
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
1 + 3 = 4
1 + 3 + 5 = 9
1 + 3 + 5 + 7 = 16
1 + 3 + 5 + 7 + 9 = 25 = 52
5 odd numbers
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
1 + 3 = 4
1 + 3 + 5 = 9
1 + 3 + 5 + 7 = 16
1 + 3 + 5 + 7 + 9 = 25 = 52
1 + 3 + 5 + 7 + 9 + 11 = 36 = 62
5 odd numbers
6 odd numbers
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
1 + 3 = 4
1 + 3 + 5 = 9
1 + 3 + 5 + 7 = 16
We observe the following pattern:
the sum of first n odd numbers is n2.
1 + 3 + 5 + 7 + 9 = 25 = 52
1 + 3 + 5 + 7 + 9 + 11 = 36 = 62
5 odd numbers
6 odd numbers
Mathematical Induction
Mathematical induction is a method for verifying
infinitely many (related) mathematical statements.
In this section, we use induction to verify formulas
for sums and inequalities.
If we add consecutive odd numbers starting from 1:
1 = 1
1 + 3 = 4
1 + 3 + 5 = 9
1 + 3 + 5 + 7 = 16
We observe the following pattern:
the sum of first n odd numbers is n2.
Using (2k – 1) for the odd numbers, we summarize
this pattern as "(2k – 1) = n2 for n = 1, 2, 3,... "k=1
n
1 + 3 + 5 + 7 + 9 = 25 = 52
1 + 3 + 5 + 7 + 9 + 11 = 36 = 62
5 odd numbers
6 odd numbers
Two observations about the above formula.
Mathematical Induction
Two observations about the above formula.
I. The formula actually consists of infinitely many
statements (assertions), one for each number n,
Mathematical Induction
Two observations about the above formula.
I. The formula actually consists of infinitely many
statements (assertions), one for each number n,
i.e. we claim that all the following statements are true.
Mathematical Induction
Two observations about the above formula.
S1: The sum of the first one odd number is 12 or that
1 = 12.
I. The formula actually consists of infinitely many
statements (assertions), one for each number n,
i.e. we claim that all the following statements are true.
Mathematical Induction
Two observations about the above formula.
S1: The sum of the first one odd number is 12 or that
1 = 12.
I. The formula actually consists of infinitely many
statements (assertions), one for each number n,
i.e. we claim that all the following statements are true.
S2: The sum of the first two odd numbers is 22 or that
1 + 3 = 22.
Mathematical Induction
Two observations about the above formula.
S1: The sum of the first one odd number is 12 or that
1 = 12.
I. The formula actually consists of infinitely many
statements (assertions), one for each number n,
i.e. we claim that all the following statements are true.
S2: The sum of the first two odd numbers is 22 or that
1 + 3 = 22.
S3: The sum of the first three odd numbers is 32 or that
1 + 3 + 5 = 32.
Mathematical Induction
Two observations about the above formula.
S1: The sum of the first one odd number is 12 or that
1 = 12.
I. The formula actually consists of infinitely many
statements (assertions), one for each number n,
i.e. we claim that all the following statements are true.
S2: The sum of the first two odd numbers is 22 or that
1 + 3 = 22.
S3: The sum of the first three odd numbers is 32 or that
1 + 3 + 5 = 32.
..
.
Sn: The sum of the first n odd numbers is n2 or that
1 + 3 + 5 + … + (2n – 1) = n2.
..
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
If infinitely many dominos are lined up such that
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
If infinitely many dominos are lined up such that
2. they are close enough so the fall of the any domino
would cause next one to fall,
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
If infinitely many dominos are lined up such that
1. the first domino falls,
2. they are close enough so the fall of the any domino
would cause next one to fall,
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
If infinitely many dominos are lined up such that
1. the first domino falls,
2. they are close enough so the fall of the any domino
would cause next one to fall, then all of them would fall.
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
(The Domino Principle) Mathematical Induction
If infinitely many dominos are lined up such that
1. the first domino falls,
2. they are close enough so the fall of the any domino
would cause next one to fall, then all of them would fall.
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
(The Domino Principle) Mathematical Induction
Given infinitely many statements S1, S2, S3,.. such that
I. S1 is true,
If infinitely many dominos are lined up such that
1. the first domino falls,
2. they are close enough so the fall of the any domino
would cause next one to fall, then all of them would fall.
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
(The Domino Principle) Mathematical Induction
Given infinitely many statements S1, S2, S3,.. such that
I. S1 is true,
II. if SN being true would imply that the next statement
SN+1 must also be true,
If infinitely many dominos are lined up such that
1. the first domino falls,
2. they are close enough so the fall of the any domino
would cause next one to fall, then all of them would fall.
Mathematical Induction
II. We may verify the first few statements easily,
but it is impossible to check all of them one by one.
Mathematical induction is a method of verifying all of
them without actually checking every one of them.
(The Domino Principle) Mathematical Induction
Given infinitely many statements S1, S2, S3,.. such that
I. S1 is true,
II. if SN being true would imply that the next statement
SN+1 must also be true,
then all the statements S1, S2, S3,.. are true.
If infinitely many dominos are lined up such that
1. the first domino falls,
2. they are close enough so the fall of the any domino
would cause next one to fall, then all of them would fall.
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. ,
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. ,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
n
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
n
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
n
We will use induction. (declaring the methodology)
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
1. verify the first statement S1 is true,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
We will use induction. (declaring the methodology)
Mathematical Induction
n
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
1. verify the first statement S1 is true,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
We will use induction. (declaring the methodology)
I. Verify its true when n = 1. (i.e S1 is true )
Mathematical Induction
n
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
1. verify the first statement S1 is true,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
n
We will use induction. (declaring the methodology)
I. Verify its true when n = 1. (i.e S1 is true )
If n = 1, we've (2k – 1) = 1k=1
1
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
1. verify the first statement S1 is true,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
n
We will use induction. (declaring the methodology)
I. Verify its true when n = 1. (i.e S1 is true )
If n = 1, we've (2k – 1) = 1 = 12
.k=1
1
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
1. verify the first statement S1 is true,
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
n
We will use induction. (declaring the methodology)
I. Verify its true when n = 1. (i.e S1 is true )
If n = 1, we've (2k – 1) = 1 = 12
. Done.k=1
1
Mathematical Induction
To use induction to verify infinitely many statements
S1, S2, S3,.. , always
0. declare that an induction argument is used,
1. verify the first statement S1 is true,
2. assume the N'th statement SN is true, use this to
verify that as a consequence, SN+1 must also be true.
Example A.
Verify that (2k – 1) = n2 for all natural numbers n.
k=1
n
We will use induction. (declaring the methodology)
I. Verify its true when n = 1. (i.e S1 is true )
If n = 1, we've (2k – 1) = 1 = 12
. Done.k=1
1
Mathematical Induction
These steps are established format when invoking the
mathematical induction and they should be followed.
II. Assume the formula works for n = N.
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
From this, verify the formula will work for n = N+1.
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1,
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1, the left hand sum is
(2k – 1)k=1
N+1
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1, the left hand sum is
(2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1
N+1
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1, the left hand sum is
(2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1
N+1
by the induction assumation this sum is N2,
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1, the left hand sum is
(2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1
N+1
by the induction assumation this sum is N2, hence
= N2 + [2(N+1) – 1]
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1, the left hand sum is
(2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1
N+1
by the induction assumation this sum is N2, hence
= N2 + [2(N+1) – 1]
= N2 + 2N + 1
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1, the left hand sum is
(2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1
N+1
by the induction assumation this sum is N2, hence
= N2 + [2(N+1) – 1]
= N2 + 2N + 1
= (N + 1)2 Done.
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Mathematical Induction
II. Assume the formula works for n = N.
(This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1
N
For n = N+1, the left hand sum is
(2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1
N+1
by the induction assumation this sum is N2, hence
= N2 + [2(N+1) – 1]
= N2 + 2N + 1
= (N + 1)2 Done.
From this, verify the formula will work for n = N+1.
(i.e. to show (2k – 1) = (N+1)2 )
k=1
N+1
Therefore (2k – 1) = n2 for all natural numbers n.k=1
n
Mathematical Induction
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
We use induction to verify this.
I. Verify its true when n = 1.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1,
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N,
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N ,
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N , then verify that it has to be
true when n = N + 1,
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N , then verify that it has to be
true when n = N + 1, i.e (N + 1) + 1 < 2N+1.
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N , then verify that it has to be
true when n = N + 1, i.e (N + 1) + 1 < 2N+1.
When n = N + 1, the left hand side is
(N + 1) + 1
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N , then verify that it has to be
true when n = N + 1, i.e (N + 1) + 1 < 2N+1.
When n = N + 1, the left hand side is
(N + 1) + 1
by the induction assumation this is < 2N
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N , then verify that it has to be
true when n = N + 1, i.e (N + 1) + 1 < 2N+1.
When n = N + 1, the left hand side is
(N + 1) + 1 < 2N + 1
by the induction assumation this is < 2N
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N , then verify that it has to be
true when n = N + 1, i.e (N + 1) + 1 < 2N+1.
When n = N + 1, the left hand side is
(N + 1) + 1 < 2N + 1 < 2N + 2N
by the induction assumation this is < 2N
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N , then verify that it has to be
true when n = N + 1, i.e (N + 1) + 1 < 2N+1.
When n = N + 1, the left hand side is
(N + 1) + 1 < 2N + 1 < 2N + 2N < 2*2N
by the induction assumation this is < 2N
We use induction to verify this.
I. Verify its true when n = 1.
If n = 1, we check that its true that 1 + 1 < 21.
Mathematical Induction
Example B.
Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
II. Assume the inequality is true for n = N, that is,
it's true that N + 1 < 2N, then verify that it has to be
true when n = N + 1, i.e (N + 1) + 1 < 2N+1.
When n = N + 1, the left hand side is
(N + 1) + 1 < 2N + 1 < 2N + 2N < 2*2N < 2N+1. Done.
by the induction assumation this is < 2N
We use induction to verify this.
In mathematics, it’s always the case that after we
observe a certain pattern first, then the induction
method is used to verify our observation.
Mathematical Induction
In other words, only after the pattern of a formula is
observed yet unproven, then the induction method is
deployed to verify the insight.
In mathematics, it’s always the case that after we
observe a certain pattern first, then the induction
method is used to verify our observation.
Mathematical Induction
In other words, only after the pattern of a formula is
observed yet unproven, then the induction method is
deployed to verify the insight.
The induction–arguments themselves do not help us
in spotting the formulas.
In mathematics, it’s always the case that after we
observe a certain pattern first, then the induction
method is used to verify our observation.
Mathematical Induction
Exercise A.
Write the following sums in the  notation.
(Do not find the sums). For example, using k as the index,
1 + 2 + 3 + 4 .. + N is k.
Mathematical Induction
k=1
N
1. Given N, the sum 12 + 22 + 32 + 42 .. + N2
2. Given K, the sum 1(2) + 2(3) + 3(4) + 4(5) .. + K(K+1)
4. Given D, the sum 3(5/2)2 + 3(6/2)2 + 3(7/2)2 + .. + 3(D/2)2
3. Given M, the sum 3(4) + 5(6) .. + (2M – 1)(2M)
5. Given D, the sum
(5/6)2 + (6/7)2 + (7/8)2 + .. + [(2D – 1)/(2D)]2
6. Given T, the sum 2(34) + 2(36) + 2(38) +.. + 2(32T)
7. Given N, the sum
1,000(e0.03) + 1,000(e0.03)2 + 1,000(e0.03)3 .. + 1,000(e0.03)N – 1
Mathematical Induction
C. Verify that each of the following formulas is true for all
positive n using mathematical induction by completing
the following steps:
Mathematical Induction
a. Tell the readers that an induction argument is coming.
b. Using k as the index, show the formula holds for n = 1.
c. Assume the formula works for the case n = N – 1
and write this “true” statement in the expanded form.
Using this fact to show the statement has to be true
for the next case when n = N
3. 1 + 2 + 3 + 4 .. + n = n (n + 1)/2
2. 1 + 3 + 5 + .. + (2n – 1) = n2
4. 2 + 6 + 10 + ... + (4n – 2) = 2n2
1. 2 + 4 + 6 + .. + 2n = n(n + 1)
5. 13 + 23 + 33 + 43 .. + n3 = n2(n + 1) 2 / 4
D. Depending on the forms of the problems, the inductive
steps maybe phrased differently.
Verify each of the following formula is true for all
positive N using mathematical induction by completing
the following steps:
Mathematical Induction
a. Tell the readers that an induction argument is coming.
b. Show the formula holds for N = 1.
c. Assuming the formula works for the case for N – 1
and write this “true” statement in the expanded form.
Using this fact to show the statement has to be true for the
next case for N.
6. 𝑘=1
𝑁
2 𝑘 = 2N+1 – 2
7. 𝑘=1
𝑁
𝑘(𝑘 + 1) = N(N + 1)(N + 2)/3
8. 𝑘=1
𝑁.
1/[k(k + 1)] = 1 – 1/(N + 1)
9. 𝑘=1
𝑁.
2/[k(k + 2)] = 1 – 2/(N + 2)
E. Verify each of the following formula is true for all
positive N using mathematical induction by completing
the following steps:
Mathematical Induction
a. Tell the readers that an induction argument is coming.
b. Show the statement is true for N = 1.
c. Assuming the statement is true for the case N – 1
and write down this “true” statement.
Then use this fact to establish that the next case for N,
the statement must also be true.
1. 3N - 1 is divisible by 2.
2. 5N - 1 is divisible by 4.
3. 7N - 1 is divisible by 6.
4. 2N3 – 3N2 + N is divisible by 6.
(Answers to the odd problems) Exercise A.
Mathematical Induction
k=1
N
1.  k2
k=2
M
3.  (2k – 1)(2k)
k=3
D
5.  [(2k – 1)/(2k)]2
k=2
N
7.  1,000(e0.03)k – 1
Exercise B.
1. 3 + 5 + … + [2(k – 1) +1] + [2k +1]
3. 2 + 5 + … + [3(n – 2) –1] + [3n –1]
5. 13 + 16 + … + [3(N – 2) –20] + [3(N – 1) –20]
7. – 7 – 10 – … – [2 – 3(2K– 2)] + [2 – 3(2K– 1)]
Exercise C.
1. We will use induction
I. Verify it’s true when n = 1
If n = 1 we have 2k = 2(1) = 2 = 1(1 + 1)k=1
1
Mathematical Induction
II. Assume the formula works for n = N – 1
i.e., 2k = 2 + 4 + 6 + … + 2(N – 1) = (N – 1)(N)k=1
N – 1
III. Verify that the formula works for n = N
For n = N, we have 2k =  2k + 2N = (N – 1)(N) + 2Nk=1
N
k=1
N – 1
= N2 – N + 2N
= N2 + N = N(N + 1)
3. We will use induction
I. Verify it’s true when n = 1
If n = 1 we have k = 1 = 1(1 + 1)/2k=1
1
II. Assume the formula works for n = N – 1
i.e., k = 1 + 2 + … + (N – 1) = (N – 1)(N)/2k=1
N – 1
III. Verify that the formula works for n = N
For n = N, we have  k =  k + N = (N – 1)N/2 + Nk=1
N
k=1
N – 1
= (N2 – N + 2N)/2
= (N2 + N)/2 = N(N + 1)/2
Mathematical Induction
5. We will use induction
I. Verify it’s true when n = 1
If n = 1 we have k3 = 13 = 1 = 12(1 + 1)2/4k=1
1
II. Assume the formula works for n = N – 1
i.e., k3 = 13 + 23 + … + (N – 1)3 = (N – 1)2N2/4k=1
N – 1
III. Verify that the formula works for n = N
For n = N, we have  k3 =  k3 + N3 = (N – 1)2N2/4 + N3
k=1
N
k=1
N – 1
= (N4 – 2N3 + N2 + 4N3)/4
= N2(N2 + 2N + 1)/4
= (N4 + 2N3 + N2)/4
= N2(N + 1)2/4
7. We will use induction
I. Verify it’s true when n = 1
If n = 1 we have  k(k + 1) = 1(1 + 1) = 2 = 1(1 + 1) (1 + 2)/3k=1
1
Exercise D.
Mathematical Induction
II. Assume the formula works for n = N – 1
i.e.,  k (k + 1) = 2 + 6 + … + (N – 1)N = (N – 1)(N)(N + 1)/3k=1
N – 1
III. Verify that the formula works for n = N
For n = N, we have  k(k + 1) =  k(k + 1) + N(N + 1)k=1
N
k=1
N – 1
= (N – 1)(N)(N + 1)/3 + N(N + 1)
= [(N – 1)(N)(N + 1) + 3N(N + 1)]/3
= N[(N – 1)(N + 1) + 3(N + 1)]/3
= N[N2 – 1 + 3N + 3]/3
= N[N2 3N + 2]/3 = N(N+1)(N+2)/3
9. The statements is not true, because when n = 1, we have
𝑘=1
1.
2/[k(k + 2)] = 2/[1(1+2)] = 2/3 = 1 – 2/(1 + 2)
Mathematical Induction
1. We will use induction
I. Verify it’s true when n = 1
If n = 1 we have 31 – 1 = 2, which is divisible by 2.
II. Assume the formula works for n = N – 1
i.e. 3N-1 – 1 is divisible by 2.
III. Verify that the formula works for n = N
For n = N, we have 3N – 1 = 3(3N-1 – 1) + 2
Exercise E.
divisible by 2 divisible by 2
3. We will use induction
I. Verify it’s true when n = 1
If n = 1 we have 71 – 1 = 6, which is divisible by 6.
II. Assume the formula works for n = N – 1
i.e. 7N-1 – 1 is divisible by 6.
III. Verify that the formula works for n = N
For n = N, we have 7N – 1 = 7(7N-1 – 1) + 7

More Related Content

What's hot

Predicates and Quantifiers
Predicates and QuantifiersPredicates and Quantifiers
Predicates and Quantifiersblaircomp2003
 
Lesson 14: Exponential Functions
Lesson 14: Exponential FunctionsLesson 14: Exponential Functions
Lesson 14: Exponential FunctionsMatthew Leingang
 
Solving systems of Linear Equations
Solving systems of Linear EquationsSolving systems of Linear Equations
Solving systems of Linear Equationsswartzje
 
mathematical induction
mathematical inductionmathematical induction
mathematical inductionankush_kumar
 
CMSC 56 | Lecture 11: Mathematical Induction
CMSC 56 | Lecture 11: Mathematical InductionCMSC 56 | Lecture 11: Mathematical Induction
CMSC 56 | Lecture 11: Mathematical Inductionallyn joy calcaben
 
Domain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptx
Domain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptxDomain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptx
Domain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptxNeomyAngelaLeono1
 
Number theory
Number theory Number theory
Number theory tes31
 
CMSC 56 | Lecture 3: Predicates & Quantifiers
CMSC 56 | Lecture 3: Predicates & QuantifiersCMSC 56 | Lecture 3: Predicates & Quantifiers
CMSC 56 | Lecture 3: Predicates & Quantifiersallyn joy calcaben
 
Exponential equations
Exponential equationsExponential equations
Exponential equationsnovember12
 
Proofs by contraposition
Proofs by contrapositionProofs by contraposition
Proofs by contrapositionAbdur Rehman
 
Pigeonhole Principle
Pigeonhole PrinciplePigeonhole Principle
Pigeonhole Principlenielsoli
 
Lesson 2: Limits and Limit Laws
Lesson 2: Limits and Limit LawsLesson 2: Limits and Limit Laws
Lesson 2: Limits and Limit LawsMatthew Leingang
 
Pigeonhole Principle,Cardinality,Countability
Pigeonhole Principle,Cardinality,CountabilityPigeonhole Principle,Cardinality,Countability
Pigeonhole Principle,Cardinality,CountabilityKiran Munir
 

What's hot (20)

Predicates and Quantifiers
Predicates and QuantifiersPredicates and Quantifiers
Predicates and Quantifiers
 
Lesson 14: Exponential Functions
Lesson 14: Exponential FunctionsLesson 14: Exponential Functions
Lesson 14: Exponential Functions
 
Solving systems of Linear Equations
Solving systems of Linear EquationsSolving systems of Linear Equations
Solving systems of Linear Equations
 
mathematical induction
mathematical inductionmathematical induction
mathematical induction
 
CMSC 56 | Lecture 11: Mathematical Induction
CMSC 56 | Lecture 11: Mathematical InductionCMSC 56 | Lecture 11: Mathematical Induction
CMSC 56 | Lecture 11: Mathematical Induction
 
Recursion DM
Recursion DMRecursion DM
Recursion DM
 
Domain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptx
Domain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptxDomain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptx
Domain-Range-Intercepts-Zeros-and-Asymptotes-of-Rational-Function.pptx
 
Number theory
Number theory Number theory
Number theory
 
CMSC 56 | Lecture 3: Predicates & Quantifiers
CMSC 56 | Lecture 3: Predicates & QuantifiersCMSC 56 | Lecture 3: Predicates & Quantifiers
CMSC 56 | Lecture 3: Predicates & Quantifiers
 
Exponential equations
Exponential equationsExponential equations
Exponential equations
 
Sequence and series
Sequence and seriesSequence and series
Sequence and series
 
Proofs by contraposition
Proofs by contrapositionProofs by contraposition
Proofs by contraposition
 
Pigeonhole Principle
Pigeonhole PrinciplePigeonhole Principle
Pigeonhole Principle
 
Relations in Discrete Math
Relations in Discrete MathRelations in Discrete Math
Relations in Discrete Math
 
Discrete Math Lecture 03: Methods of Proof
Discrete Math Lecture 03: Methods of ProofDiscrete Math Lecture 03: Methods of Proof
Discrete Math Lecture 03: Methods of Proof
 
Proof in Mathematics
Proof in MathematicsProof in Mathematics
Proof in Mathematics
 
Proof by contradiction
Proof by contradictionProof by contradiction
Proof by contradiction
 
Lesson 2: Limits and Limit Laws
Lesson 2: Limits and Limit LawsLesson 2: Limits and Limit Laws
Lesson 2: Limits and Limit Laws
 
Pigeonhole Principle,Cardinality,Countability
Pigeonhole Principle,Cardinality,CountabilityPigeonhole Principle,Cardinality,Countability
Pigeonhole Principle,Cardinality,Countability
 
Limit of functions
Limit of functionsLimit of functions
Limit of functions
 

Viewers also liked

Math induction principle (slides)
Math induction principle (slides)Math induction principle (slides)
Math induction principle (slides)IIUM
 
Mathematical induction and divisibility rules
Mathematical induction and divisibility rulesMathematical induction and divisibility rules
Mathematical induction and divisibility rulesDawood Faheem Abbasi
 
Mathematical induction
Mathematical inductionMathematical induction
Mathematical inductionsonia -
 
11 x1 t14 09 mathematical induction 2 (2013)
11 x1 t14 09 mathematical induction 2 (2013)11 x1 t14 09 mathematical induction 2 (2013)
11 x1 t14 09 mathematical induction 2 (2013)Nigel Simmons
 
11X1 T14 08 mathematical induction 1 (2011)
11X1 T14 08 mathematical induction 1 (2011)11X1 T14 08 mathematical induction 1 (2011)
11X1 T14 08 mathematical induction 1 (2011)Nigel Simmons
 
Iteration, induction, and recursion
Iteration, induction, and recursionIteration, induction, and recursion
Iteration, induction, and recursionMohammed Hussein
 
X2 t08 02 induction (2013)
X2 t08 02 induction (2013)X2 t08 02 induction (2013)
X2 t08 02 induction (2013)Nigel Simmons
 
Lecture 5 limit laws
Lecture 5   limit lawsLecture 5   limit laws
Lecture 5 limit lawsnjit-ronbrown
 
RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...
RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...
RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...RuleML
 
RuleML2015: How to combine event stream reasoning with transactions for the...
RuleML2015:   How to combine event stream reasoning with transactions for the...RuleML2015:   How to combine event stream reasoning with transactions for the...
RuleML2015: How to combine event stream reasoning with transactions for the...RuleML
 
History of Induction and Recursion B
History of Induction and Recursion B History of Induction and Recursion B
History of Induction and Recursion B Damien MacFarland
 
AP Chemistry Chapter 11 Sample Exercises
AP Chemistry Chapter 11 Sample ExercisesAP Chemistry Chapter 11 Sample Exercises
AP Chemistry Chapter 11 Sample ExercisesJane Hamze
 
RuleML 2015: When Processes Rule Events
RuleML 2015: When Processes Rule EventsRuleML 2015: When Processes Rule Events
RuleML 2015: When Processes Rule EventsRuleML
 
Induction and Decision Tree Learning (Part 1)
Induction and Decision Tree Learning (Part 1)Induction and Decision Tree Learning (Part 1)
Induction and Decision Tree Learning (Part 1)butest
 
Conic sections day one
Conic sections day oneConic sections day one
Conic sections day oneJessica Garcia
 
Lesson 10 conic sections - hyperbola
Lesson 10    conic sections - hyperbolaLesson 10    conic sections - hyperbola
Lesson 10 conic sections - hyperbolaJean Leano
 

Viewers also liked (20)

Math induction principle (slides)
Math induction principle (slides)Math induction principle (slides)
Math induction principle (slides)
 
Mathematical induction and divisibility rules
Mathematical induction and divisibility rulesMathematical induction and divisibility rules
Mathematical induction and divisibility rules
 
Mathematical induction
Mathematical inductionMathematical induction
Mathematical induction
 
Per4 induction
Per4 inductionPer4 induction
Per4 induction
 
11 x1 t14 09 mathematical induction 2 (2013)
11 x1 t14 09 mathematical induction 2 (2013)11 x1 t14 09 mathematical induction 2 (2013)
11 x1 t14 09 mathematical induction 2 (2013)
 
11X1 T14 08 mathematical induction 1 (2011)
11X1 T14 08 mathematical induction 1 (2011)11X1 T14 08 mathematical induction 1 (2011)
11X1 T14 08 mathematical induction 1 (2011)
 
Iteration, induction, and recursion
Iteration, induction, and recursionIteration, induction, and recursion
Iteration, induction, and recursion
 
5.1 Induction
5.1 Induction5.1 Induction
5.1 Induction
 
X2 t08 02 induction (2013)
X2 t08 02 induction (2013)X2 t08 02 induction (2013)
X2 t08 02 induction (2013)
 
Theorems on limits
Theorems on limitsTheorems on limits
Theorems on limits
 
Lecture 5 limit laws
Lecture 5   limit lawsLecture 5   limit laws
Lecture 5 limit laws
 
RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...
RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...
RuleML 2015: Semantics of Notation3 Logic: A Solution for Implicit Quantifica...
 
RuleML2015: How to combine event stream reasoning with transactions for the...
RuleML2015:   How to combine event stream reasoning with transactions for the...RuleML2015:   How to combine event stream reasoning with transactions for the...
RuleML2015: How to combine event stream reasoning with transactions for the...
 
History of Induction and Recursion B
History of Induction and Recursion B History of Induction and Recursion B
History of Induction and Recursion B
 
AP Chemistry Chapter 11 Sample Exercises
AP Chemistry Chapter 11 Sample ExercisesAP Chemistry Chapter 11 Sample Exercises
AP Chemistry Chapter 11 Sample Exercises
 
RuleML 2015: When Processes Rule Events
RuleML 2015: When Processes Rule EventsRuleML 2015: When Processes Rule Events
RuleML 2015: When Processes Rule Events
 
Induction and Decision Tree Learning (Part 1)
Induction and Decision Tree Learning (Part 1)Induction and Decision Tree Learning (Part 1)
Induction and Decision Tree Learning (Part 1)
 
Conic sections day one
Conic sections day oneConic sections day one
Conic sections day one
 
1515 conics
1515 conics1515 conics
1515 conics
 
Lesson 10 conic sections - hyperbola
Lesson 10    conic sections - hyperbolaLesson 10    conic sections - hyperbola
Lesson 10 conic sections - hyperbola
 

Similar to 5.4 mathematical induction

MATHEMATICAL INDUCTION.ppt
MATHEMATICAL INDUCTION.pptMATHEMATICAL INDUCTION.ppt
MATHEMATICAL INDUCTION.pptMarjorie Malveda
 
Verifying Solutions of a Linear System
Verifying Solutions of a Linear SystemVerifying Solutions of a Linear System
Verifying Solutions of a Linear Systemdmidgette
 
Chapter 3 - Problem Solving.pdf
Chapter 3 - Problem Solving.pdfChapter 3 - Problem Solving.pdf
Chapter 3 - Problem Solving.pdfMinaSaflor
 
DIGITAL TEXT BOOK
DIGITAL TEXT BOOKDIGITAL TEXT BOOK
DIGITAL TEXT BOOKbintu55
 
Mathematical Statistics Assignment Help
Mathematical Statistics Assignment HelpMathematical Statistics Assignment Help
Mathematical Statistics Assignment HelpExcel Homework Help
 
mathematicalinductionanddivisibilityrules-160711105713.pdf
mathematicalinductionanddivisibilityrules-160711105713.pdfmathematicalinductionanddivisibilityrules-160711105713.pdf
mathematicalinductionanddivisibilityrules-160711105713.pdfBhanuCharan9
 
Proof of the collatz conjecture
Proof of the collatz conjectureProof of the collatz conjecture
Proof of the collatz conjectureChris De Corte
 
7th maths-1.concept , addition and subtraction properties of intergers-sangh
7th maths-1.concept , addition and subtraction properties of intergers-sangh7th maths-1.concept , addition and subtraction properties of intergers-sangh
7th maths-1.concept , addition and subtraction properties of intergers-sanghLiveOnlineClassesInd
 
7th maths-1.concept , addition and subtraction properties of intergers
7th maths-1.concept , addition and subtraction properties of intergers7th maths-1.concept , addition and subtraction properties of intergers
7th maths-1.concept , addition and subtraction properties of intergersLiveOnlineClassesInd
 
Math lecture 7 (Arithmetic Sequence)
Math lecture 7 (Arithmetic Sequence)Math lecture 7 (Arithmetic Sequence)
Math lecture 7 (Arithmetic Sequence)Osama Zahid
 
Module 3_Problem Solving With Logic.pptx
Module 3_Problem Solving With Logic.pptxModule 3_Problem Solving With Logic.pptx
Module 3_Problem Solving With Logic.pptxClaudineBaladjay1
 
The Complexity Of Primality Testing
The Complexity Of Primality TestingThe Complexity Of Primality Testing
The Complexity Of Primality TestingMohammad Elsheikh
 
1.1 patterns & inductive reasoning
1.1 patterns & inductive reasoning1.1 patterns & inductive reasoning
1.1 patterns & inductive reasoningvickihoover
 

Similar to 5.4 mathematical induction (20)

MATHEMATICAL INDUCTION.ppt
MATHEMATICAL INDUCTION.pptMATHEMATICAL INDUCTION.ppt
MATHEMATICAL INDUCTION.ppt
 
Alex Shen ...
Alex Shen                                                                    ...Alex Shen                                                                    ...
Alex Shen ...
 
Analysis.pptx
Analysis.pptxAnalysis.pptx
Analysis.pptx
 
4AMT122-PART 1-SLIDES.pptx
4AMT122-PART 1-SLIDES.pptx4AMT122-PART 1-SLIDES.pptx
4AMT122-PART 1-SLIDES.pptx
 
Mathematical Statistics Assignment Help
Mathematical Statistics Assignment HelpMathematical Statistics Assignment Help
Mathematical Statistics Assignment Help
 
Verifying Solutions of a Linear System
Verifying Solutions of a Linear SystemVerifying Solutions of a Linear System
Verifying Solutions of a Linear System
 
Buacm 3
Buacm 3Buacm 3
Buacm 3
 
Chapter 3 - Problem Solving.pdf
Chapter 3 - Problem Solving.pdfChapter 3 - Problem Solving.pdf
Chapter 3 - Problem Solving.pdf
 
DIGITAL TEXT BOOK
DIGITAL TEXT BOOKDIGITAL TEXT BOOK
DIGITAL TEXT BOOK
 
Mathematical Statistics Assignment Help
Mathematical Statistics Assignment HelpMathematical Statistics Assignment Help
Mathematical Statistics Assignment Help
 
mathematicalinductionanddivisibilityrules-160711105713.pdf
mathematicalinductionanddivisibilityrules-160711105713.pdfmathematicalinductionanddivisibilityrules-160711105713.pdf
mathematicalinductionanddivisibilityrules-160711105713.pdf
 
Proof of the collatz conjecture
Proof of the collatz conjectureProof of the collatz conjecture
Proof of the collatz conjecture
 
7th maths-1.concept , addition and subtraction properties of intergers-sangh
7th maths-1.concept , addition and subtraction properties of intergers-sangh7th maths-1.concept , addition and subtraction properties of intergers-sangh
7th maths-1.concept , addition and subtraction properties of intergers-sangh
 
7th maths-1.concept , addition and subtraction properties of intergers
7th maths-1.concept , addition and subtraction properties of intergers7th maths-1.concept , addition and subtraction properties of intergers
7th maths-1.concept , addition and subtraction properties of intergers
 
1
11
1
 
Math lecture 7 (Arithmetic Sequence)
Math lecture 7 (Arithmetic Sequence)Math lecture 7 (Arithmetic Sequence)
Math lecture 7 (Arithmetic Sequence)
 
Module 3_Problem Solving With Logic.pptx
Module 3_Problem Solving With Logic.pptxModule 3_Problem Solving With Logic.pptx
Module 3_Problem Solving With Logic.pptx
 
Crt
CrtCrt
Crt
 
The Complexity Of Primality Testing
The Complexity Of Primality TestingThe Complexity Of Primality Testing
The Complexity Of Primality Testing
 
1.1 patterns & inductive reasoning
1.1 patterns & inductive reasoning1.1 patterns & inductive reasoning
1.1 patterns & inductive reasoning
 

More from math260

36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptx36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptxmath260
 
35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptx35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptxmath260
 
18Ellipses-x.pptx
18Ellipses-x.pptx18Ellipses-x.pptx
18Ellipses-x.pptxmath260
 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions xmath260
 
10.5 more on language of functions x
10.5 more on language of functions x10.5 more on language of functions x
10.5 more on language of functions xmath260
 
1 exponents yz
1 exponents yz1 exponents yz
1 exponents yzmath260
 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions xmath260
 
8 inequalities and sign charts x
8 inequalities and sign charts x8 inequalities and sign charts x
8 inequalities and sign charts xmath260
 
7 sign charts of factorable formulas y
7 sign charts of factorable formulas y7 sign charts of factorable formulas y
7 sign charts of factorable formulas ymath260
 
19 more parabolas a&amp; hyperbolas (optional) x
19 more parabolas a&amp; hyperbolas (optional) x19 more parabolas a&amp; hyperbolas (optional) x
19 more parabolas a&amp; hyperbolas (optional) xmath260
 
18 ellipses x
18 ellipses x18 ellipses x
18 ellipses xmath260
 
17 conic sections circles-x
17 conic sections circles-x17 conic sections circles-x
17 conic sections circles-xmath260
 
16 slopes and difference quotient x
16 slopes and difference quotient x16 slopes and difference quotient x
16 slopes and difference quotient xmath260
 
15 translations of graphs x
15 translations of graphs x15 translations of graphs x
15 translations of graphs xmath260
 
14 graphs of factorable rational functions x
14 graphs of factorable rational functions x14 graphs of factorable rational functions x
14 graphs of factorable rational functions xmath260
 
13 graphs of factorable polynomials x
13 graphs of factorable polynomials x13 graphs of factorable polynomials x
13 graphs of factorable polynomials xmath260
 
12 graphs of second degree functions x
12 graphs of second degree functions x12 graphs of second degree functions x
12 graphs of second degree functions xmath260
 
10 rectangular coordinate system x
10 rectangular coordinate system x10 rectangular coordinate system x
10 rectangular coordinate system xmath260
 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions xmath260
 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions xmath260
 

More from math260 (20)

36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptx36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptx
 
35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptx35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptx
 
18Ellipses-x.pptx
18Ellipses-x.pptx18Ellipses-x.pptx
18Ellipses-x.pptx
 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions x
 
10.5 more on language of functions x
10.5 more on language of functions x10.5 more on language of functions x
10.5 more on language of functions x
 
1 exponents yz
1 exponents yz1 exponents yz
1 exponents yz
 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions x
 
8 inequalities and sign charts x
8 inequalities and sign charts x8 inequalities and sign charts x
8 inequalities and sign charts x
 
7 sign charts of factorable formulas y
7 sign charts of factorable formulas y7 sign charts of factorable formulas y
7 sign charts of factorable formulas y
 
19 more parabolas a&amp; hyperbolas (optional) x
19 more parabolas a&amp; hyperbolas (optional) x19 more parabolas a&amp; hyperbolas (optional) x
19 more parabolas a&amp; hyperbolas (optional) x
 
18 ellipses x
18 ellipses x18 ellipses x
18 ellipses x
 
17 conic sections circles-x
17 conic sections circles-x17 conic sections circles-x
17 conic sections circles-x
 
16 slopes and difference quotient x
16 slopes and difference quotient x16 slopes and difference quotient x
16 slopes and difference quotient x
 
15 translations of graphs x
15 translations of graphs x15 translations of graphs x
15 translations of graphs x
 
14 graphs of factorable rational functions x
14 graphs of factorable rational functions x14 graphs of factorable rational functions x
14 graphs of factorable rational functions x
 
13 graphs of factorable polynomials x
13 graphs of factorable polynomials x13 graphs of factorable polynomials x
13 graphs of factorable polynomials x
 
12 graphs of second degree functions x
12 graphs of second degree functions x12 graphs of second degree functions x
12 graphs of second degree functions x
 
10 rectangular coordinate system x
10 rectangular coordinate system x10 rectangular coordinate system x
10 rectangular coordinate system x
 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions x
 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions x
 

Recently uploaded

Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Zilliz
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDropbox
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAndrey Devyatkin
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingEdi Saputra
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontologyjohnbeverley2021
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Angeliki Cooney
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityWSO2
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Jeffrey Haguewood
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...apidays
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobeapidays
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...apidays
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesrafiqahmad00786416
 

Recently uploaded (20)

Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital Adaptability
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 

5.4 mathematical induction

  • 2. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements.
  • 3. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities.
  • 4. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1:
  • 5. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1
  • 6. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1 1 + 3 = 4
  • 7. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1 1 + 3 = 4 1 + 3 + 5 = 9
  • 8. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1 1 + 3 = 4 1 + 3 + 5 = 9 1 + 3 + 5 + 7 = 16
  • 9. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1 1 + 3 = 4 1 + 3 + 5 = 9 1 + 3 + 5 + 7 = 16 1 + 3 + 5 + 7 + 9 = 25 = 52 5 odd numbers
  • 10. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1 1 + 3 = 4 1 + 3 + 5 = 9 1 + 3 + 5 + 7 = 16 1 + 3 + 5 + 7 + 9 = 25 = 52 1 + 3 + 5 + 7 + 9 + 11 = 36 = 62 5 odd numbers 6 odd numbers
  • 11. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1 1 + 3 = 4 1 + 3 + 5 = 9 1 + 3 + 5 + 7 = 16 We observe the following pattern: the sum of first n odd numbers is n2. 1 + 3 + 5 + 7 + 9 = 25 = 52 1 + 3 + 5 + 7 + 9 + 11 = 36 = 62 5 odd numbers 6 odd numbers
  • 12. Mathematical Induction Mathematical induction is a method for verifying infinitely many (related) mathematical statements. In this section, we use induction to verify formulas for sums and inequalities. If we add consecutive odd numbers starting from 1: 1 = 1 1 + 3 = 4 1 + 3 + 5 = 9 1 + 3 + 5 + 7 = 16 We observe the following pattern: the sum of first n odd numbers is n2. Using (2k – 1) for the odd numbers, we summarize this pattern as "(2k – 1) = n2 for n = 1, 2, 3,... "k=1 n 1 + 3 + 5 + 7 + 9 = 25 = 52 1 + 3 + 5 + 7 + 9 + 11 = 36 = 62 5 odd numbers 6 odd numbers
  • 13. Two observations about the above formula. Mathematical Induction
  • 14. Two observations about the above formula. I. The formula actually consists of infinitely many statements (assertions), one for each number n, Mathematical Induction
  • 15. Two observations about the above formula. I. The formula actually consists of infinitely many statements (assertions), one for each number n, i.e. we claim that all the following statements are true. Mathematical Induction
  • 16. Two observations about the above formula. S1: The sum of the first one odd number is 12 or that 1 = 12. I. The formula actually consists of infinitely many statements (assertions), one for each number n, i.e. we claim that all the following statements are true. Mathematical Induction
  • 17. Two observations about the above formula. S1: The sum of the first one odd number is 12 or that 1 = 12. I. The formula actually consists of infinitely many statements (assertions), one for each number n, i.e. we claim that all the following statements are true. S2: The sum of the first two odd numbers is 22 or that 1 + 3 = 22. Mathematical Induction
  • 18. Two observations about the above formula. S1: The sum of the first one odd number is 12 or that 1 = 12. I. The formula actually consists of infinitely many statements (assertions), one for each number n, i.e. we claim that all the following statements are true. S2: The sum of the first two odd numbers is 22 or that 1 + 3 = 22. S3: The sum of the first three odd numbers is 32 or that 1 + 3 + 5 = 32. Mathematical Induction
  • 19. Two observations about the above formula. S1: The sum of the first one odd number is 12 or that 1 = 12. I. The formula actually consists of infinitely many statements (assertions), one for each number n, i.e. we claim that all the following statements are true. S2: The sum of the first two odd numbers is 22 or that 1 + 3 = 22. S3: The sum of the first three odd numbers is 32 or that 1 + 3 + 5 = 32. .. . Sn: The sum of the first n odd numbers is n2 or that 1 + 3 + 5 + … + (2n – 1) = n2. .. Mathematical Induction
  • 20. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical Induction
  • 21. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. Mathematical Induction
  • 22. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. If infinitely many dominos are lined up such that Mathematical Induction
  • 23. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. If infinitely many dominos are lined up such that 2. they are close enough so the fall of the any domino would cause next one to fall, Mathematical Induction
  • 24. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. If infinitely many dominos are lined up such that 1. the first domino falls, 2. they are close enough so the fall of the any domino would cause next one to fall, Mathematical Induction
  • 25. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. If infinitely many dominos are lined up such that 1. the first domino falls, 2. they are close enough so the fall of the any domino would cause next one to fall, then all of them would fall. Mathematical Induction
  • 26. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. (The Domino Principle) Mathematical Induction If infinitely many dominos are lined up such that 1. the first domino falls, 2. they are close enough so the fall of the any domino would cause next one to fall, then all of them would fall. Mathematical Induction
  • 27. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. (The Domino Principle) Mathematical Induction Given infinitely many statements S1, S2, S3,.. such that I. S1 is true, If infinitely many dominos are lined up such that 1. the first domino falls, 2. they are close enough so the fall of the any domino would cause next one to fall, then all of them would fall. Mathematical Induction
  • 28. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. (The Domino Principle) Mathematical Induction Given infinitely many statements S1, S2, S3,.. such that I. S1 is true, II. if SN being true would imply that the next statement SN+1 must also be true, If infinitely many dominos are lined up such that 1. the first domino falls, 2. they are close enough so the fall of the any domino would cause next one to fall, then all of them would fall. Mathematical Induction
  • 29. II. We may verify the first few statements easily, but it is impossible to check all of them one by one. Mathematical induction is a method of verifying all of them without actually checking every one of them. (The Domino Principle) Mathematical Induction Given infinitely many statements S1, S2, S3,.. such that I. S1 is true, II. if SN being true would imply that the next statement SN+1 must also be true, then all the statements S1, S2, S3,.. are true. If infinitely many dominos are lined up such that 1. the first domino falls, 2. they are close enough so the fall of the any domino would cause next one to fall, then all of them would fall. Mathematical Induction
  • 30. To use induction to verify infinitely many statements S1, S2, S3,.. , Mathematical Induction
  • 31. To use induction to verify infinitely many statements S1, S2, S3,.. , Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 n Mathematical Induction
  • 32. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 n Mathematical Induction
  • 33. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 n We will use induction. (declaring the methodology) Mathematical Induction
  • 34. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, 1. verify the first statement S1 is true, Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 We will use induction. (declaring the methodology) Mathematical Induction n
  • 35. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, 1. verify the first statement S1 is true, Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 We will use induction. (declaring the methodology) I. Verify its true when n = 1. (i.e S1 is true ) Mathematical Induction n
  • 36. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, 1. verify the first statement S1 is true, Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 n We will use induction. (declaring the methodology) I. Verify its true when n = 1. (i.e S1 is true ) If n = 1, we've (2k – 1) = 1k=1 1 Mathematical Induction
  • 37. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, 1. verify the first statement S1 is true, Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 n We will use induction. (declaring the methodology) I. Verify its true when n = 1. (i.e S1 is true ) If n = 1, we've (2k – 1) = 1 = 12 .k=1 1 Mathematical Induction
  • 38. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, 1. verify the first statement S1 is true, Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 n We will use induction. (declaring the methodology) I. Verify its true when n = 1. (i.e S1 is true ) If n = 1, we've (2k – 1) = 1 = 12 . Done.k=1 1 Mathematical Induction
  • 39. To use induction to verify infinitely many statements S1, S2, S3,.. , always 0. declare that an induction argument is used, 1. verify the first statement S1 is true, 2. assume the N'th statement SN is true, use this to verify that as a consequence, SN+1 must also be true. Example A. Verify that (2k – 1) = n2 for all natural numbers n. k=1 n We will use induction. (declaring the methodology) I. Verify its true when n = 1. (i.e S1 is true ) If n = 1, we've (2k – 1) = 1 = 12 . Done.k=1 1 Mathematical Induction These steps are established format when invoking the mathematical induction and they should be followed.
  • 40. II. Assume the formula works for n = N. Mathematical Induction
  • 41. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N Mathematical Induction
  • 42. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N From this, verify the formula will work for n = N+1. Mathematical Induction
  • 43. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 44. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 45. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, the left hand sum is (2k – 1)k=1 N+1 From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 46. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, the left hand sum is (2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1 N+1 From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 47. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, the left hand sum is (2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1 N+1 by the induction assumation this sum is N2, From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 48. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, the left hand sum is (2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1 N+1 by the induction assumation this sum is N2, hence = N2 + [2(N+1) – 1] From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 49. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, the left hand sum is (2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1 N+1 by the induction assumation this sum is N2, hence = N2 + [2(N+1) – 1] = N2 + 2N + 1 From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 50. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, the left hand sum is (2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1 N+1 by the induction assumation this sum is N2, hence = N2 + [2(N+1) – 1] = N2 + 2N + 1 = (N + 1)2 Done. From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Mathematical Induction
  • 51. II. Assume the formula works for n = N. (This means that (2k – 1) = 1 + 3 + .. + (2N – 1) = N2 is true.)k=1 N For n = N+1, the left hand sum is (2k – 1) = 1 + 3 + .. + (2N – 1) + [2(N+1) – 1]k=1 N+1 by the induction assumation this sum is N2, hence = N2 + [2(N+1) – 1] = N2 + 2N + 1 = (N + 1)2 Done. From this, verify the formula will work for n = N+1. (i.e. to show (2k – 1) = (N+1)2 ) k=1 N+1 Therefore (2k – 1) = n2 for all natural numbers n.k=1 n Mathematical Induction
  • 52. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,…
  • 53. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… We use induction to verify this.
  • 54. I. Verify its true when n = 1. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… We use induction to verify this.
  • 55. I. Verify its true when n = 1. If n = 1, Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… We use induction to verify this.
  • 56. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… We use induction to verify this.
  • 57. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, We use induction to verify this.
  • 58. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , We use induction to verify this.
  • 59. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , then verify that it has to be true when n = N + 1, We use induction to verify this.
  • 60. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , then verify that it has to be true when n = N + 1, i.e (N + 1) + 1 < 2N+1. We use induction to verify this.
  • 61. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , then verify that it has to be true when n = N + 1, i.e (N + 1) + 1 < 2N+1. When n = N + 1, the left hand side is (N + 1) + 1 We use induction to verify this.
  • 62. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , then verify that it has to be true when n = N + 1, i.e (N + 1) + 1 < 2N+1. When n = N + 1, the left hand side is (N + 1) + 1 by the induction assumation this is < 2N We use induction to verify this.
  • 63. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , then verify that it has to be true when n = N + 1, i.e (N + 1) + 1 < 2N+1. When n = N + 1, the left hand side is (N + 1) + 1 < 2N + 1 by the induction assumation this is < 2N We use induction to verify this.
  • 64. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , then verify that it has to be true when n = N + 1, i.e (N + 1) + 1 < 2N+1. When n = N + 1, the left hand side is (N + 1) + 1 < 2N + 1 < 2N + 2N by the induction assumation this is < 2N We use induction to verify this.
  • 65. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N , then verify that it has to be true when n = N + 1, i.e (N + 1) + 1 < 2N+1. When n = N + 1, the left hand side is (N + 1) + 1 < 2N + 1 < 2N + 2N < 2*2N by the induction assumation this is < 2N We use induction to verify this.
  • 66. I. Verify its true when n = 1. If n = 1, we check that its true that 1 + 1 < 21. Mathematical Induction Example B. Verify that n + 1 < 2n for all numbers n =1, 2, 3,… II. Assume the inequality is true for n = N, that is, it's true that N + 1 < 2N, then verify that it has to be true when n = N + 1, i.e (N + 1) + 1 < 2N+1. When n = N + 1, the left hand side is (N + 1) + 1 < 2N + 1 < 2N + 2N < 2*2N < 2N+1. Done. by the induction assumation this is < 2N We use induction to verify this.
  • 67. In mathematics, it’s always the case that after we observe a certain pattern first, then the induction method is used to verify our observation. Mathematical Induction
  • 68. In other words, only after the pattern of a formula is observed yet unproven, then the induction method is deployed to verify the insight. In mathematics, it’s always the case that after we observe a certain pattern first, then the induction method is used to verify our observation. Mathematical Induction
  • 69. In other words, only after the pattern of a formula is observed yet unproven, then the induction method is deployed to verify the insight. The induction–arguments themselves do not help us in spotting the formulas. In mathematics, it’s always the case that after we observe a certain pattern first, then the induction method is used to verify our observation. Mathematical Induction
  • 70. Exercise A. Write the following sums in the  notation. (Do not find the sums). For example, using k as the index, 1 + 2 + 3 + 4 .. + N is k. Mathematical Induction k=1 N 1. Given N, the sum 12 + 22 + 32 + 42 .. + N2 2. Given K, the sum 1(2) + 2(3) + 3(4) + 4(5) .. + K(K+1) 4. Given D, the sum 3(5/2)2 + 3(6/2)2 + 3(7/2)2 + .. + 3(D/2)2 3. Given M, the sum 3(4) + 5(6) .. + (2M – 1)(2M) 5. Given D, the sum (5/6)2 + (6/7)2 + (7/8)2 + .. + [(2D – 1)/(2D)]2 6. Given T, the sum 2(34) + 2(36) + 2(38) +.. + 2(32T) 7. Given N, the sum 1,000(e0.03) + 1,000(e0.03)2 + 1,000(e0.03)3 .. + 1,000(e0.03)N – 1
  • 72. C. Verify that each of the following formulas is true for all positive n using mathematical induction by completing the following steps: Mathematical Induction a. Tell the readers that an induction argument is coming. b. Using k as the index, show the formula holds for n = 1. c. Assume the formula works for the case n = N – 1 and write this “true” statement in the expanded form. Using this fact to show the statement has to be true for the next case when n = N 3. 1 + 2 + 3 + 4 .. + n = n (n + 1)/2 2. 1 + 3 + 5 + .. + (2n – 1) = n2 4. 2 + 6 + 10 + ... + (4n – 2) = 2n2 1. 2 + 4 + 6 + .. + 2n = n(n + 1) 5. 13 + 23 + 33 + 43 .. + n3 = n2(n + 1) 2 / 4
  • 73. D. Depending on the forms of the problems, the inductive steps maybe phrased differently. Verify each of the following formula is true for all positive N using mathematical induction by completing the following steps: Mathematical Induction a. Tell the readers that an induction argument is coming. b. Show the formula holds for N = 1. c. Assuming the formula works for the case for N – 1 and write this “true” statement in the expanded form. Using this fact to show the statement has to be true for the next case for N. 6. 𝑘=1 𝑁 2 𝑘 = 2N+1 – 2 7. 𝑘=1 𝑁 𝑘(𝑘 + 1) = N(N + 1)(N + 2)/3 8. 𝑘=1 𝑁. 1/[k(k + 1)] = 1 – 1/(N + 1) 9. 𝑘=1 𝑁. 2/[k(k + 2)] = 1 – 2/(N + 2)
  • 74. E. Verify each of the following formula is true for all positive N using mathematical induction by completing the following steps: Mathematical Induction a. Tell the readers that an induction argument is coming. b. Show the statement is true for N = 1. c. Assuming the statement is true for the case N – 1 and write down this “true” statement. Then use this fact to establish that the next case for N, the statement must also be true. 1. 3N - 1 is divisible by 2. 2. 5N - 1 is divisible by 4. 3. 7N - 1 is divisible by 6. 4. 2N3 – 3N2 + N is divisible by 6.
  • 75. (Answers to the odd problems) Exercise A. Mathematical Induction k=1 N 1.  k2 k=2 M 3.  (2k – 1)(2k) k=3 D 5.  [(2k – 1)/(2k)]2 k=2 N 7.  1,000(e0.03)k – 1 Exercise B. 1. 3 + 5 + … + [2(k – 1) +1] + [2k +1] 3. 2 + 5 + … + [3(n – 2) –1] + [3n –1] 5. 13 + 16 + … + [3(N – 2) –20] + [3(N – 1) –20] 7. – 7 – 10 – … – [2 – 3(2K– 2)] + [2 – 3(2K– 1)] Exercise C. 1. We will use induction I. Verify it’s true when n = 1 If n = 1 we have 2k = 2(1) = 2 = 1(1 + 1)k=1 1
  • 76. Mathematical Induction II. Assume the formula works for n = N – 1 i.e., 2k = 2 + 4 + 6 + … + 2(N – 1) = (N – 1)(N)k=1 N – 1 III. Verify that the formula works for n = N For n = N, we have 2k =  2k + 2N = (N – 1)(N) + 2Nk=1 N k=1 N – 1 = N2 – N + 2N = N2 + N = N(N + 1) 3. We will use induction I. Verify it’s true when n = 1 If n = 1 we have k = 1 = 1(1 + 1)/2k=1 1 II. Assume the formula works for n = N – 1 i.e., k = 1 + 2 + … + (N – 1) = (N – 1)(N)/2k=1 N – 1 III. Verify that the formula works for n = N For n = N, we have  k =  k + N = (N – 1)N/2 + Nk=1 N k=1 N – 1 = (N2 – N + 2N)/2 = (N2 + N)/2 = N(N + 1)/2
  • 77. Mathematical Induction 5. We will use induction I. Verify it’s true when n = 1 If n = 1 we have k3 = 13 = 1 = 12(1 + 1)2/4k=1 1 II. Assume the formula works for n = N – 1 i.e., k3 = 13 + 23 + … + (N – 1)3 = (N – 1)2N2/4k=1 N – 1 III. Verify that the formula works for n = N For n = N, we have  k3 =  k3 + N3 = (N – 1)2N2/4 + N3 k=1 N k=1 N – 1 = (N4 – 2N3 + N2 + 4N3)/4 = N2(N2 + 2N + 1)/4 = (N4 + 2N3 + N2)/4 = N2(N + 1)2/4 7. We will use induction I. Verify it’s true when n = 1 If n = 1 we have  k(k + 1) = 1(1 + 1) = 2 = 1(1 + 1) (1 + 2)/3k=1 1 Exercise D.
  • 78. Mathematical Induction II. Assume the formula works for n = N – 1 i.e.,  k (k + 1) = 2 + 6 + … + (N – 1)N = (N – 1)(N)(N + 1)/3k=1 N – 1 III. Verify that the formula works for n = N For n = N, we have  k(k + 1) =  k(k + 1) + N(N + 1)k=1 N k=1 N – 1 = (N – 1)(N)(N + 1)/3 + N(N + 1) = [(N – 1)(N)(N + 1) + 3N(N + 1)]/3 = N[(N – 1)(N + 1) + 3(N + 1)]/3 = N[N2 – 1 + 3N + 3]/3 = N[N2 3N + 2]/3 = N(N+1)(N+2)/3 9. The statements is not true, because when n = 1, we have 𝑘=1 1. 2/[k(k + 2)] = 2/[1(1+2)] = 2/3 = 1 – 2/(1 + 2)
  • 79. Mathematical Induction 1. We will use induction I. Verify it’s true when n = 1 If n = 1 we have 31 – 1 = 2, which is divisible by 2. II. Assume the formula works for n = N – 1 i.e. 3N-1 – 1 is divisible by 2. III. Verify that the formula works for n = N For n = N, we have 3N – 1 = 3(3N-1 – 1) + 2 Exercise E. divisible by 2 divisible by 2 3. We will use induction I. Verify it’s true when n = 1 If n = 1 we have 71 – 1 = 6, which is divisible by 6. II. Assume the formula works for n = N – 1 i.e. 7N-1 – 1 is divisible by 6. III. Verify that the formula works for n = N For n = N, we have 7N – 1 = 7(7N-1 – 1) + 7