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Measures Of Central
Tendency
Mean ,Median, Mode
Measures Of Central
Tendency
• Measures of central tendency provides a very
convenient way of describing a set of scores with a
single number that describes the PERFORMANCE
of the group.
• It is also defined as a single value that is used to
describe the CENTER of the data.
• There are the commonly used measures of central
tendency .these are the following:
1. Mean
2. Median
3. mode
MEAN
• It is the most commonly used measure of the center
of data
• It is also referred as the ARITHMETIC AVERAGE
• Calculation of sample mean
1. AM = Σ x = x1 + x2 + x3 + … xn
N N
MEAN
• Calculation of the Mean for Ungrouped Data
2. AM= Σ x
N
3. AM= Σ f x
N
MEAN
• Example :
• Scores of 15 students in Mathematics quiz consist
of 25 items.
• The highest score is 25 and the lowest score is 10.
Here are
• the scores: 25, 20, 18, 18, 17, 15, 15, 15, 14, 14,
13, 12, 12,10, 10. Find the mean in the following
scores.
scores 25 20 18 18 17 15 15 15 14 14 13 12 12 10 10
AM = Σ x
N
AM=228
15
=15.2
Analysis: The average performance of 15 students
who participated in mathematics quiz consisting of
25 items is 15.20. The implication of this is that
student who got scores below 15.2 did not perform
well in the said examination. Students who got
scores higher than 15.2 performed well in the
examination compared to the performance of the
whole class.
MEAN
Mean for Grouped Data
• Grouped data are the data or scores that are
arranged in a frequency distribution.
• Frequency is the number of observations falling in a
category.
• Frequency distribution is the arrangement of scores
according to category of classes including the
frequency
MEDIAN
• Median is what divides the scores in the distribution
into two equal parts.
• Fifty percent (50%) lies below the median value and
50% lies above the median value.
• It is also known as the middle score or the 50th
percentile.
MEDIAN
Median of Ungrouped Data
1. Arrange the scores (from lowest to highest or
highest to lowest).
2. Determine the middle most score in a distribution if
n is an odd number and get the average of the two
middle most scores if n is an even number.
MEDIAN
Example 1: Find the median score of 7 students in an
English class.
SCOR
E
19 17 16 15 10 5 2
MEDIAN=15
MEDIAN
Example: Find the median score of 8 students in an
English class.
score 30 19 17 16 15 10 5 2
Median=16+15
2
=15.5
MEDIAN
• Median of Grouped Data
• Formula:L+n/2-C*I
fm
• MC = median class is a category containing the n/2
• L = lower boundary of the median class (MC)
• C = cumulative frequency before the median class if the
scores are arranged from lowest to highest value
• fm = frequency of the median class
• I= size of the class interval
MEDIAN
1. Complete the table for cumulative frequency
2. Get n/2 of the scores in the distribution so that you
can identify MC
3. Determine L,C,fm,I
4. Solve the median using the formula
Example: Scores of 40 students in a science class consist of 60
items and they are tabulated below. The highest score is 54 and
the lowest score is 10.
X F Cf
10-14 5 5
15-19 2 7
20-24 3 10
25-29 5 15
30-34 2 17
35-39 9 26
40-44 6 32
45-49 3 35
50-54 5 40
N=40
Solution:
n/2=40/2=20
The category containing=
n/2 is 35-39
L of the MC =35
L=34.5
C=17
Fm=9
I=5
• L+n/2-C*I
fm
34.5+20-17*5
9
=34.5+15/9
=36.17
median
Properties of the Median
• It may not be an actual observation in the data set.
• It can be applied in ordinal level.
• It is not affected by extreme values because median is a
positional measure.
• When to Use the Median
• The exact midpoint of the score distribution is desired.
• There are extreme scores in the distribution.
mode
• The mode or the modal score is a score or scores that
occurred most in the distribution.
• It is classified as unimodal, bimodal, trimodal or mulitimodal.
• Unimodal is a distribution of scores that consists of only one
mode
• Bimodal is a distribution of scores that consists of two modes.
• Trimodal is a distribution of scores that consists of three
• modes or multimodal is a distribution of scores that
• consists of more than two modes.
Mode for Grouped Data
• In solving the mode value in grouped data, use the
formula:
d1
M=L+d1+d2 *I
L=lower boundary of the modal class
MC=is a category containing the highest frequency
d1=difference between the frequency of the modal
class and the frequency above it, when the scores
are arranged from lowest to highest.
• d2 = difference between the frequency of the modal
class and the frequency below it, when the scores
are arranged from lowest to highest.
• I = size of the class interval
Example: Scores of 40 students in a science class
consist of 60 items and
they are tabulated below.
X
10-14 5
15-19 2
20-24 3
25-29 5
30-34 2
35-39 9
40-44 6
45-49 3
50-54 5
N= 40
Model class=35-39
L of MC=35
L=34.5
D1=9-2=7
D2=9-6=3
I=5
l=+d1/d1+d2*I
34.5+7/7+3*5
34.5+35/10
Mode=38
mode
Properties of the Mode
• It can be used when the data are qualitative as well as
quantitative.
• It may not be unique.
• It is affected by extreme values
• It may not exist
When to Use the Mode
• When the “typical” value is desired.
• When the data set is measured on a nominal scale.

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Measures of central tendency

  • 2. Measures Of Central Tendency • Measures of central tendency provides a very convenient way of describing a set of scores with a single number that describes the PERFORMANCE of the group. • It is also defined as a single value that is used to describe the CENTER of the data. • There are the commonly used measures of central tendency .these are the following: 1. Mean 2. Median 3. mode
  • 3. MEAN • It is the most commonly used measure of the center of data • It is also referred as the ARITHMETIC AVERAGE • Calculation of sample mean 1. AM = Σ x = x1 + x2 + x3 + … xn N N
  • 4. MEAN • Calculation of the Mean for Ungrouped Data 2. AM= Σ x N 3. AM= Σ f x N
  • 5. MEAN • Example : • Scores of 15 students in Mathematics quiz consist of 25 items. • The highest score is 25 and the lowest score is 10. Here are • the scores: 25, 20, 18, 18, 17, 15, 15, 15, 14, 14, 13, 12, 12,10, 10. Find the mean in the following scores.
  • 6. scores 25 20 18 18 17 15 15 15 14 14 13 12 12 10 10 AM = Σ x N AM=228 15 =15.2
  • 7. Analysis: The average performance of 15 students who participated in mathematics quiz consisting of 25 items is 15.20. The implication of this is that student who got scores below 15.2 did not perform well in the said examination. Students who got scores higher than 15.2 performed well in the examination compared to the performance of the whole class.
  • 8. MEAN Mean for Grouped Data • Grouped data are the data or scores that are arranged in a frequency distribution. • Frequency is the number of observations falling in a category. • Frequency distribution is the arrangement of scores according to category of classes including the frequency
  • 9. MEDIAN • Median is what divides the scores in the distribution into two equal parts. • Fifty percent (50%) lies below the median value and 50% lies above the median value. • It is also known as the middle score or the 50th percentile.
  • 10. MEDIAN Median of Ungrouped Data 1. Arrange the scores (from lowest to highest or highest to lowest). 2. Determine the middle most score in a distribution if n is an odd number and get the average of the two middle most scores if n is an even number.
  • 11. MEDIAN Example 1: Find the median score of 7 students in an English class. SCOR E 19 17 16 15 10 5 2 MEDIAN=15
  • 12. MEDIAN Example: Find the median score of 8 students in an English class. score 30 19 17 16 15 10 5 2 Median=16+15 2 =15.5
  • 13. MEDIAN • Median of Grouped Data • Formula:L+n/2-C*I fm • MC = median class is a category containing the n/2 • L = lower boundary of the median class (MC) • C = cumulative frequency before the median class if the scores are arranged from lowest to highest value • fm = frequency of the median class • I= size of the class interval
  • 14. MEDIAN 1. Complete the table for cumulative frequency 2. Get n/2 of the scores in the distribution so that you can identify MC 3. Determine L,C,fm,I 4. Solve the median using the formula
  • 15. Example: Scores of 40 students in a science class consist of 60 items and they are tabulated below. The highest score is 54 and the lowest score is 10. X F Cf 10-14 5 5 15-19 2 7 20-24 3 10 25-29 5 15 30-34 2 17 35-39 9 26 40-44 6 32 45-49 3 35 50-54 5 40 N=40
  • 16. Solution: n/2=40/2=20 The category containing= n/2 is 35-39 L of the MC =35 L=34.5 C=17 Fm=9 I=5 • L+n/2-C*I fm 34.5+20-17*5 9 =34.5+15/9 =36.17
  • 17. median Properties of the Median • It may not be an actual observation in the data set. • It can be applied in ordinal level. • It is not affected by extreme values because median is a positional measure. • When to Use the Median • The exact midpoint of the score distribution is desired. • There are extreme scores in the distribution.
  • 18. mode • The mode or the modal score is a score or scores that occurred most in the distribution. • It is classified as unimodal, bimodal, trimodal or mulitimodal. • Unimodal is a distribution of scores that consists of only one mode • Bimodal is a distribution of scores that consists of two modes. • Trimodal is a distribution of scores that consists of three • modes or multimodal is a distribution of scores that • consists of more than two modes.
  • 19. Mode for Grouped Data • In solving the mode value in grouped data, use the formula: d1 M=L+d1+d2 *I L=lower boundary of the modal class MC=is a category containing the highest frequency d1=difference between the frequency of the modal class and the frequency above it, when the scores are arranged from lowest to highest.
  • 20. • d2 = difference between the frequency of the modal class and the frequency below it, when the scores are arranged from lowest to highest. • I = size of the class interval
  • 21. Example: Scores of 40 students in a science class consist of 60 items and they are tabulated below. X 10-14 5 15-19 2 20-24 3 25-29 5 30-34 2 35-39 9 40-44 6 45-49 3 50-54 5 N= 40
  • 22. Model class=35-39 L of MC=35 L=34.5 D1=9-2=7 D2=9-6=3 I=5 l=+d1/d1+d2*I 34.5+7/7+3*5 34.5+35/10 Mode=38
  • 23. mode Properties of the Mode • It can be used when the data are qualitative as well as quantitative. • It may not be unique. • It is affected by extreme values • It may not exist When to Use the Mode • When the “typical” value is desired. • When the data set is measured on a nominal scale.