SlideShare ist ein Scribd-Unternehmen logo
1 von 69
1
Measures of Central Tendency
2
3
Determine the mean of
the following.
4
5
6
7
8
9
10
11
12
13
14
Measures of Central Tendency of
GROUPED DATA
15
Grouped Data
Grouped data are the data or scores
that are arranged in a frequency
distribution.
16
Grouped Data
17
Mean
The mean (also known as the
arithmetic mean) is the most
commonly used measure of central
position. It is used to describe a set of
data where the measures cluster or
concentrate at a point.18
Mean
Formula:
19
mfX
X
n


f frequency
mX classmark
n sum of frequency
20
X mean
mfX
X
n

Where:
21
Illustrative Example:
Calculate the mean of the Mid-year Scores of
Students in Mathematics.
Score Frequency
41-45 1
36-40 8
31-35 8
26-30 14
21-25 7
16-20 2
Mid-year Test scores of students in Mathematics
22
Solution
1. Find the midpoint or class mark ( ) of each
class or category.
mX
2
m
LL UL
X


Scores
41-45 1
36-40 8
31-35 8
26-30 14
21-25 7
16-20 2
23
Solution
1. Find the midpoint or class mark ( ) of each
class or category.
mX
2
m
LL UL
X


Scores
41-45 1 43
36-40 8
31-35 8
26-30 14
21-25 7
16-20 2
24
Solution
1. Find the midpoint or class mark ( ) of each
class or category.
mX
2
m
LL UL
X


Scores
41-45 1 43
36-40 8 38
31-35 8
26-30 14
21-25 7
16-20 2
25
Solution
1. Find the midpoint or class mark ( ) of each
class or category.
mX
2
m
LL UL
X


Scores
41-45 1 43
36-40 8 38
31-35 8 33
26-30 14
21-25 7
16-20 2
26
Solution
1. Find the midpoint or class mark ( ) of each
class or category.
mX
2
m
LL UL
X


Scores
41-45 1 43
36-40 8 38
31-35 8 33
26-30 14 28
21-25 7
16-20 2
27
Solution
1. Find the midpoint or class mark ( ) of each
class or category.
mX
2
m
LL UL
X


Scores
41-45 1 43
36-40 8 38
31-35 8 33
26-30 14 28
21-25 7 23
16-20 2
28
Solution
1. Find the midpoint or class mark ( ) of each
class or category.
mX
2
m
LL UL
X


Scores
41-45 1 43
36-40 8 38
31-35 8 33
26-30 14 28
21-25 7 23
16-20 2 18
29
Solution
2. Multiply the frequency and the corresponding
class mark . fXm
Scores Frequency
(f )
41-45 1 43
36-40 8 38
31-35 8 33
26-30 14 28
21-25 7 23
16-20 2 18
30
Solution
2. Multiply the frequency and the corresponding
class mark . fXm
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38
31-35 8 33
26-30 14 28
21-25 7 23
16-20 2 18
31
Solution
2. Multiply the frequency and the corresponding
class mark . fXm
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33
26-30 14 28
21-25 7 23
16-20 2 18
32
Solution
2. Multiply the frequency and the corresponding
class mark . fXm
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33 264
26-30 14 28
21-25 7 23
16-20 2 18
33
Solution
2. Multiply the frequency and the corresponding
class mark . fXm
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33 264
26-30 14 28 392
21-25 7 23
16-20 2 18
34
Solution
2. Multiply the frequency and the corresponding
class mark . fXm
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33 264
26-30 14 28 392
21-25 7 23 161
16-20 2 18
35
Solution
2. Multiply the frequency and the corresponding
class mark . fXm
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33 264
26-30 14 28 392
21-25 7 23 161
16-20 2 18 36
36
Solution
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33 264
26-30 14 28 392
21-25 7 23 161
16-20 2 18 36
3. Find the sum of the results in step 2. fXm
37
Solution
3. Find the sum of the results in step 2.
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33 264
26-30 14 28 392
21-25 7 23 161
16-20 2 18 36
fXm
Solution
4. Solve the mean using the formula.
Scores Frequency
(f )
41-45 1 43 43
36-40 8 38 304
31-35 8 33 264
26-30 14 28 392
21-25 7 23 161
16-20 2 18 36
n=40
Substitution
Therefore, the
mean of Mid-
year test is 30.
mfX
X
n


1,200
40

30X 
39
Let’s practice: Find the mean weight of
Grade 8 Students.
Weight in kg Frequency
75-79 1
70-74 4
65-69 10
60-64 14
55-59 21
50-54 15
45-49 14
40-44 1
Weight in kg Frequency (f)
75-79 1
70-74 4
65-69 10
60-64 14
55-59 21
50-54 15
45-49 14
40-44 1
40
Weight in kg Frequency (f)
75-79 1 77
70-74 4
65-69 10
60-64 14
55-59 21
50-54 15
45-49 14
40-44 1
41
Weight in kg Frequency (f)
75-79 1 77
70-74 4 72
65-69 10
60-64 14
55-59 21
50-54 15
45-49 14
40-44 1
42
Weight in kg Frequency (f)
75-79 1 77
70-74 4 72
65-69 10 67
60-64 14
55-59 21
50-54 15
45-49 14
40-44 1
43
Weight in kg Frequency (f)
75-79 1 77
70-74 4 72
65-69 10 67
60-64 14 62
55-59 21
50-54 15
45-49 14
40-44 1
44
Weight in kg Frequency (f)
75-79 1 77
70-74 4 72
65-69 10 67
60-64 14 62
55-59 21 57
50-54 15
45-49 14
40-44 1
45
Weight in kg Frequency (f)
75-79 1 77
70-74 4 72
65-69 10 67
60-64 14 62
55-59 21 57
50-54 15 52
45-49 14
40-44 1
46
Weight in kg Frequency (f)
75-79 1 77
70-74 4 72
65-69 10 67
60-64 14 62
55-59 21 57
50-54 15 52
45-49 14 47
40-44 1
47
Weight in kg Frequency (f)
75-79 1 77
70-74 4 72
65-69 10 67
60-64 14 62
55-59 21 57
50-54 15 52
45-49 14 47
40-44 1 42
48
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72
65-69 10 67
60-64 14 62
55-59 21 57
50-54 15 52
45-49 14 47
40-44 1 42
49
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67
60-64 14 62
55-59 21 57
50-54 15 52
45-49 14 47
40-44 1 42
50
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62
55-59 21 57
50-54 15 52
45-49 14 47
40-44 1 42
51
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62 868
55-59 21 57
50-54 15 52
45-49 14 47
40-44 1 42
52
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62 868
55-59 21 57 1197
50-54 15 52
45-49 14 47
40-44 1 42
53
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62 868
55-59 21 57 1197
50-54 15 52 780
45-49 14 47
40-44 1 42
54
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62 868
55-59 21 57 1197
50-54 15 52 780
45-49 14 47 658
40-44 1 42
55
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62 868
55-59 21 57 1197
50-54 15 52 780
45-49 14 47 658
40-44 1 42 42
56
Weight in kg Frequency (f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62 868
55-59 21 57 1197
50-54 15 52 780
45-49 14 47 658
40-44 1 42 42
57
Therefore, the
mean weight is
57.25
Weight in
kg
Frequency
(f)
75-79 1 77 77
70-74 4 72 288
65-69 10 67 670
60-64 14 62 868
55-59 21 57 1197
50-54 15 52 780
45-49 14 47 658
40-44 1 42 42
mfX
X
n


4580
80

57.25X 
59
Generalization
60
Generalization
The mean (also known as the
arithmetic mean) is the most
commonly used measure of central
position. It is used to describe a set
of data where the measures cluster
or concentrate at a point.
61
Formula
mfX
X
n


62
Group Work
CRITERIA
5 4 3 2 1
63
Group Work
CRITERIA
5 4 3 2 1
ACCURACY 100% of the steps
and solutions
have no
mathematical
errors.
Almost all (90-
99%) of the steps
and solutions
have no
mathematical
errors.
Almost all (85-
89%) of the steps
and solutions
have no
mathematical
errors.
Most (75-84%) of
the steps and
solutions have
no mathematical
errors.
Less than 75% of
the steps and
solutions have
mathematical
errors.
64
Group Work
CRITERIA
5 4 3 2 1
ORGANIZATION It uses an
appropriate and
complete strategy
for solving the
problem. Uses clear
and effective
diagrams and/or
tables.
It uses complete
strategy for solving
the problem. Uses
creative diagrams
and/or tables.
It uses strategy for
solving the
problem. Uses
diagrams and/or
tables.
It uses an
inappropriate
strategy or
application of
strategy unclear.
There is limited
use or misuse of
diagrams and/or
tables.
It has no particular
strategy for
solving the
problem. It does
not show use of
diagrams nor
tables.
65
Group Work
CRITERIA
5 4 3 2 1
DELIVERY There is a clear and
effective explanation
of the solution. All
steps are included so
the audience does
not have to infer how
the task was
completed.
Mathematical
representation is
actively used as a
means of
communicating ideas,
and precise and
appropriate
mathematical
terminology.
There is a clear
explanation and
appropriate use of
accurate
mathematical
representation. There
is effective use of
mathematical
terminology.
There is explanation
and mathematical
representation.
There is
mathematical
terminology
There is an
incomplete
explanation; it is not
clearly represented.
There is some use of
appropriate
mathematical
representation and
terminology to the
task.
There is no
explanation of the
solutions. The
explanation cannot
be understood, or is
unrelated to the
task. There is no use
or inappropriate use
of mathematical
representation and
terminology to the
task.
TIMER
10 minutes
End
67
Assignment
1. A telecommunications company is conducting a study on the
average number text messages send per day by high school
students in Marikina. A random sample of 50 college students
from the said area is taken. Find the mean of the data set.
Class Interval Frequency
30-34 8
25-29 10
20-24 16
15-19 9
10-14 7
68
2. Study on Median for Grouped Data
a.Describe Median.
b.What is the formula in computing the
median for grouped data?
Reference: Mathematics Learner’s Module by
Emmanuel P. Abunzo
Pages 564-580
69

Weitere ähnliche Inhalte

Was ist angesagt?

frequency distribution table
frequency distribution tablefrequency distribution table
frequency distribution tableMonie Ali
 
Determining measures of central tendency for grouped data
Determining measures of central tendency for grouped dataDetermining measures of central tendency for grouped data
Determining measures of central tendency for grouped dataAlona Hall
 
PROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptx
PROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptxPROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptx
PROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptxReinabelleMarfilMarq
 
Equation of a circle
Equation of a circleEquation of a circle
Equation of a circlevhughes5
 
DECILE : MEASURES OF POSITION FOR GROUPED DATA
DECILE : MEASURES OF POSITION FOR GROUPED DATADECILE : MEASURES OF POSITION FOR GROUPED DATA
DECILE : MEASURES OF POSITION FOR GROUPED DATAChuckry Maunes
 
Measures of Central Tendency: Ungrouped and Grouped
Measures of Central Tendency: Ungrouped and GroupedMeasures of Central Tendency: Ungrouped and Grouped
Measures of Central Tendency: Ungrouped and GroupedMaryGraceRecaaAgusti
 
Standard Deviation and Variance
Standard Deviation and VarianceStandard Deviation and Variance
Standard Deviation and VarianceJufil Hombria
 
Lesson 2 percentiles
Lesson 2   percentilesLesson 2   percentiles
Lesson 2 percentileskarisashley
 
Rational Equations and Inequalities
 Rational Equations and Inequalities  Rational Equations and Inequalities
Rational Equations and Inequalities pemey13
 
Long division, synthetic division, remainder theorem and factor theorem
Long division, synthetic division, remainder theorem and factor theoremLong division, synthetic division, remainder theorem and factor theorem
Long division, synthetic division, remainder theorem and factor theoremJohn Rome Aranas
 
QUARTILES : MEASURES OF POSITION FOR GROUPED DATA
QUARTILES : MEASURES OF POSITION FOR GROUPED DATAQUARTILES : MEASURES OF POSITION FOR GROUPED DATA
QUARTILES : MEASURES OF POSITION FOR GROUPED DATAChuckry Maunes
 
Rational functions
Rational functionsRational functions
Rational functionszozima
 
Summative Test on Measures of Position
Summative Test on Measures of PositionSummative Test on Measures of Position
Summative Test on Measures of PositionJoey Valdriz
 
Geometric Sequence
Geometric SequenceGeometric Sequence
Geometric SequenceJoey Valdriz
 

Was ist angesagt? (20)

Measures of variability grouped data
Measures of variability grouped dataMeasures of variability grouped data
Measures of variability grouped data
 
frequency distribution table
frequency distribution tablefrequency distribution table
frequency distribution table
 
Polynomial function
Polynomial functionPolynomial function
Polynomial function
 
4. parameter and statistic
4. parameter and statistic4. parameter and statistic
4. parameter and statistic
 
Determining measures of central tendency for grouped data
Determining measures of central tendency for grouped dataDetermining measures of central tendency for grouped data
Determining measures of central tendency for grouped data
 
PROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptx
PROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptxPROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptx
PROBABILITY OF MUTUALLY EXCLUSIVE EVENTS final.pptx
 
Equation of a circle
Equation of a circleEquation of a circle
Equation of a circle
 
DECILE : MEASURES OF POSITION FOR GROUPED DATA
DECILE : MEASURES OF POSITION FOR GROUPED DATADECILE : MEASURES OF POSITION FOR GROUPED DATA
DECILE : MEASURES OF POSITION FOR GROUPED DATA
 
Measures of Central Tendency: Ungrouped and Grouped
Measures of Central Tendency: Ungrouped and GroupedMeasures of Central Tendency: Ungrouped and Grouped
Measures of Central Tendency: Ungrouped and Grouped
 
Standard Deviation and Variance
Standard Deviation and VarianceStandard Deviation and Variance
Standard Deviation and Variance
 
Lesson 2 percentiles
Lesson 2   percentilesLesson 2   percentiles
Lesson 2 percentiles
 
Rational Equations and Inequalities
 Rational Equations and Inequalities  Rational Equations and Inequalities
Rational Equations and Inequalities
 
Long division, synthetic division, remainder theorem and factor theorem
Long division, synthetic division, remainder theorem and factor theoremLong division, synthetic division, remainder theorem and factor theorem
Long division, synthetic division, remainder theorem and factor theorem
 
QUARTILES : MEASURES OF POSITION FOR GROUPED DATA
QUARTILES : MEASURES OF POSITION FOR GROUPED DATAQUARTILES : MEASURES OF POSITION FOR GROUPED DATA
QUARTILES : MEASURES OF POSITION FOR GROUPED DATA
 
Harmonic sequence
Harmonic sequenceHarmonic sequence
Harmonic sequence
 
Rational functions
Rational functionsRational functions
Rational functions
 
Summation Notation
Summation NotationSummation Notation
Summation Notation
 
Summative Test on Measures of Position
Summative Test on Measures of PositionSummative Test on Measures of Position
Summative Test on Measures of Position
 
Geometric Sequence
Geometric SequenceGeometric Sequence
Geometric Sequence
 
Quadratic functions
Quadratic functionsQuadratic functions
Quadratic functions
 

Andere mochten auch

Grouped Mean Median Mode
Grouped Mean Median ModeGrouped Mean Median Mode
Grouped Mean Median ModePassy World
 
Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency Jan Nah
 
Measures of location for grouped data
Measures of location for grouped dataMeasures of location for grouped data
Measures of location for grouped dataJordan Rey Infante
 
Measures of location for grouped data
Measures of location for grouped dataMeasures of location for grouped data
Measures of location for grouped dataJordan Rey Infante
 
3.4 Measures of Position
3.4 Measures of Position3.4 Measures of Position
3.4 Measures of Positionmlong24
 
Percentage Rank
Percentage RankPercentage Rank
Percentage RankEn Em
 
Mathematics 10 Learner’s Material Unit 4
Mathematics 10 Learner’s Material Unit 4Mathematics 10 Learner’s Material Unit 4
Mathematics 10 Learner’s Material Unit 4PRINTDESK by Dan
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statisticsAbhinav yadav
 
Estimated Mean Presentation
Estimated Mean PresentationEstimated Mean Presentation
Estimated Mean PresentationRichard Foxton
 
Ch21 22 data analysis and interpretation
Ch21 22 data analysis and interpretationCh21 22 data analysis and interpretation
Ch21 22 data analysis and interpretationJay Tanna
 
Measuresofcentraltendencygrpdata
MeasuresofcentraltendencygrpdataMeasuresofcentraltendencygrpdata
MeasuresofcentraltendencygrpdataChie Pegollo
 
Lesson 3 measures of central tendency
Lesson 3   measures of central tendencyLesson 3   measures of central tendency
Lesson 3 measures of central tendencykarisashley
 
11.9 dependent and independent events
11.9 dependent and independent events11.9 dependent and independent events
11.9 dependent and independent eventsRachel
 
Advanced statistics Lesson 1
Advanced statistics Lesson 1Advanced statistics Lesson 1
Advanced statistics Lesson 1Cliffed Echavez
 
Chapter 3 260110 044503
Chapter 3 260110 044503Chapter 3 260110 044503
Chapter 3 260110 044503guest25d353
 
Statistik Chapter 2
Statistik Chapter 2Statistik Chapter 2
Statistik Chapter 2WanBK Leo
 
Difference between grouped and ungrouped data
Difference between grouped and ungrouped dataDifference between grouped and ungrouped data
Difference between grouped and ungrouped dataAtiq Rehman
 

Andere mochten auch (20)

Grouped Mean Median Mode
Grouped Mean Median ModeGrouped Mean Median Mode
Grouped Mean Median Mode
 
Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency Mean, Median, Mode: Measures of Central Tendency
Mean, Median, Mode: Measures of Central Tendency
 
Measures of location for grouped data
Measures of location for grouped dataMeasures of location for grouped data
Measures of location for grouped data
 
Measures of position
Measures of positionMeasures of position
Measures of position
 
Measures of location for grouped data
Measures of location for grouped dataMeasures of location for grouped data
Measures of location for grouped data
 
Fractiles
FractilesFractiles
Fractiles
 
3.4 Measures of Position
3.4 Measures of Position3.4 Measures of Position
3.4 Measures of Position
 
Percentage Rank
Percentage RankPercentage Rank
Percentage Rank
 
Mathematics 10 Learner’s Material Unit 4
Mathematics 10 Learner’s Material Unit 4Mathematics 10 Learner’s Material Unit 4
Mathematics 10 Learner’s Material Unit 4
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
 
Estimated Mean Presentation
Estimated Mean PresentationEstimated Mean Presentation
Estimated Mean Presentation
 
Ch21 22 data analysis and interpretation
Ch21 22 data analysis and interpretationCh21 22 data analysis and interpretation
Ch21 22 data analysis and interpretation
 
Measuresofcentraltendencygrpdata
MeasuresofcentraltendencygrpdataMeasuresofcentraltendencygrpdata
Measuresofcentraltendencygrpdata
 
Lesson 3 measures of central tendency
Lesson 3   measures of central tendencyLesson 3   measures of central tendency
Lesson 3 measures of central tendency
 
11.9 dependent and independent events
11.9 dependent and independent events11.9 dependent and independent events
11.9 dependent and independent events
 
Advanced statistics Lesson 1
Advanced statistics Lesson 1Advanced statistics Lesson 1
Advanced statistics Lesson 1
 
Module 2 statistics
Module 2   statisticsModule 2   statistics
Module 2 statistics
 
Chapter 3 260110 044503
Chapter 3 260110 044503Chapter 3 260110 044503
Chapter 3 260110 044503
 
Statistik Chapter 2
Statistik Chapter 2Statistik Chapter 2
Statistik Chapter 2
 
Difference between grouped and ungrouped data
Difference between grouped and ungrouped dataDifference between grouped and ungrouped data
Difference between grouped and ungrouped data
 

Ähnlich wie Mean for Grouped Data

Statistics Assignment
Statistics AssignmentStatistics Assignment
Statistics AssignmentMishal Roy
 
Module 2 statistics
Module 2   statisticsModule 2   statistics
Module 2 statisticsdionesioable
 
..............Pascua_Renlie Jane_01.pptx
..............Pascua_Renlie Jane_01.pptx..............Pascua_Renlie Jane_01.pptx
..............Pascua_Renlie Jane_01.pptxrenliejanepedronan
 
An overview of statistics management with excel
An overview of statistics management with excelAn overview of statistics management with excel
An overview of statistics management with excelKRISHANACHOUDHARY1
 
Arithmetic Mean in Business Statistics
Arithmetic Mean in Business StatisticsArithmetic Mean in Business Statistics
Arithmetic Mean in Business Statisticsmuthukrishnaveni anand
 
Assessment of Learning 2 (Overview)
Assessment of Learning 2 (Overview)Assessment of Learning 2 (Overview)
Assessment of Learning 2 (Overview)Caroline Lace
 
Chapter 7 statistics
Chapter 7  statisticsChapter 7  statistics
Chapter 7 statisticsatiqah ayie
 
lesson 3 presentation of data and frequency distribution
lesson 3 presentation of data and frequency distributionlesson 3 presentation of data and frequency distribution
lesson 3 presentation of data and frequency distributionNerz Baldres
 
Analysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptxAnalysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptxAeonneFlux
 
Basic Statistical Measures
Basic Statistical MeasuresBasic Statistical Measures
Basic Statistical MeasuresShubham Mehta
 
Education Assessment in Learnings 1.pptx
Education Assessment in Learnings 1.pptxEducation Assessment in Learnings 1.pptx
Education Assessment in Learnings 1.pptxRayLorenzOrtega
 
QUARTILE AND DECILE OF GROUPED DATA
QUARTILE AND DECILE OF GROUPED DATAQUARTILE AND DECILE OF GROUPED DATA
QUARTILE AND DECILE OF GROUPED DATAJENNYROSEDALIGDIG1
 
3_-frequency_distribution.pptx
3_-frequency_distribution.pptx3_-frequency_distribution.pptx
3_-frequency_distribution.pptxitzsudipto99
 
Group 3 measures of central tendency and variation - (mean, median, mode, ra...
Group 3  measures of central tendency and variation - (mean, median, mode, ra...Group 3  measures of central tendency and variation - (mean, median, mode, ra...
Group 3 measures of central tendency and variation - (mean, median, mode, ra...reymartyvette_0611
 
Biostatichomeworks
Biostatichomeworks Biostatichomeworks
Biostatichomeworks raveen mayi
 
CRUDE OIL - Statistics for Business Management
CRUDE OIL - Statistics for Business ManagementCRUDE OIL - Statistics for Business Management
CRUDE OIL - Statistics for Business ManagementMayankAgrawal205
 

Ähnlich wie Mean for Grouped Data (20)

Statistics Assignment
Statistics AssignmentStatistics Assignment
Statistics Assignment
 
Module 2 statistics
Module 2   statisticsModule 2   statistics
Module 2 statistics
 
..............Pascua_Renlie Jane_01.pptx
..............Pascua_Renlie Jane_01.pptx..............Pascua_Renlie Jane_01.pptx
..............Pascua_Renlie Jane_01.pptx
 
STATISTICS
STATISTICSSTATISTICS
STATISTICS
 
An overview of statistics management with excel
An overview of statistics management with excelAn overview of statistics management with excel
An overview of statistics management with excel
 
Arithmetic Mean in Business Statistics
Arithmetic Mean in Business StatisticsArithmetic Mean in Business Statistics
Arithmetic Mean in Business Statistics
 
S3 pn
S3 pnS3 pn
S3 pn
 
Assessment of Learning 2 (Overview)
Assessment of Learning 2 (Overview)Assessment of Learning 2 (Overview)
Assessment of Learning 2 (Overview)
 
Chapter 7 statistics
Chapter 7  statisticsChapter 7  statistics
Chapter 7 statistics
 
lesson 3 presentation of data and frequency distribution
lesson 3 presentation of data and frequency distributionlesson 3 presentation of data and frequency distribution
lesson 3 presentation of data and frequency distribution
 
Analysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptxAnalysis and interpretation of Assessment.pptx
Analysis and interpretation of Assessment.pptx
 
Lecture 1.pptx
Lecture 1.pptxLecture 1.pptx
Lecture 1.pptx
 
Basic Statistical Measures
Basic Statistical MeasuresBasic Statistical Measures
Basic Statistical Measures
 
Education Assessment in Learnings 1.pptx
Education Assessment in Learnings 1.pptxEducation Assessment in Learnings 1.pptx
Education Assessment in Learnings 1.pptx
 
Mean of grouped data
Mean of grouped dataMean of grouped data
Mean of grouped data
 
QUARTILE AND DECILE OF GROUPED DATA
QUARTILE AND DECILE OF GROUPED DATAQUARTILE AND DECILE OF GROUPED DATA
QUARTILE AND DECILE OF GROUPED DATA
 
3_-frequency_distribution.pptx
3_-frequency_distribution.pptx3_-frequency_distribution.pptx
3_-frequency_distribution.pptx
 
Group 3 measures of central tendency and variation - (mean, median, mode, ra...
Group 3  measures of central tendency and variation - (mean, median, mode, ra...Group 3  measures of central tendency and variation - (mean, median, mode, ra...
Group 3 measures of central tendency and variation - (mean, median, mode, ra...
 
Biostatichomeworks
Biostatichomeworks Biostatichomeworks
Biostatichomeworks
 
CRUDE OIL - Statistics for Business Management
CRUDE OIL - Statistics for Business ManagementCRUDE OIL - Statistics for Business Management
CRUDE OIL - Statistics for Business Management
 

Kürzlich hochgeladen

Unit 3 Emotional Intelligence and Spiritual Intelligence.pdf
Unit 3 Emotional Intelligence and Spiritual Intelligence.pdfUnit 3 Emotional Intelligence and Spiritual Intelligence.pdf
Unit 3 Emotional Intelligence and Spiritual Intelligence.pdfDr Vijay Vishwakarma
 
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...Nguyen Thanh Tu Collection
 
How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17Celine George
 
Wellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptxWellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptxJisc
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024Elizabeth Walsh
 
Towards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptxTowards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptxJisc
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentationcamerronhm
 
Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)Jisc
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxRamakrishna Reddy Bijjam
 
REMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxREMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxDr. Ravikiran H M Gowda
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxheathfieldcps1
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Single or Multiple melodic lines structure
Single or Multiple melodic lines structureSingle or Multiple melodic lines structure
Single or Multiple melodic lines structuredhanjurrannsibayan2
 
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...ZurliaSoop
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.christianmathematics
 
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...Pooja Bhuva
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and ModificationsMJDuyan
 
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxEsquimalt MFRC
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfPoh-Sun Goh
 

Kürzlich hochgeladen (20)

Unit 3 Emotional Intelligence and Spiritual Intelligence.pdf
Unit 3 Emotional Intelligence and Spiritual Intelligence.pdfUnit 3 Emotional Intelligence and Spiritual Intelligence.pdf
Unit 3 Emotional Intelligence and Spiritual Intelligence.pdf
 
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
 
How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17
 
Wellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptxWellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptx
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024
 
Towards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptxTowards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptx
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)Jamworks pilot and AI at Jisc (20/03/2024)
Jamworks pilot and AI at Jisc (20/03/2024)
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 
REMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxREMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptx
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Single or Multiple melodic lines structure
Single or Multiple melodic lines structureSingle or Multiple melodic lines structure
Single or Multiple melodic lines structure
 
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.
 
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
Sensory_Experience_and_Emotional_Resonance_in_Gabriel_Okaras_The_Piano_and_Th...
 
Spatium Project Simulation student brief
Spatium Project Simulation student briefSpatium Project Simulation student brief
Spatium Project Simulation student brief
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and Modifications
 
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdf
 

Mean for Grouped Data

  • 1. 1
  • 2. Measures of Central Tendency 2
  • 3. 3 Determine the mean of the following.
  • 4. 4
  • 5. 5
  • 6. 6
  • 7. 7
  • 8. 8
  • 9. 9
  • 10. 10
  • 11. 11
  • 12. 12
  • 13. 13
  • 14. 14 Measures of Central Tendency of GROUPED DATA
  • 16. Grouped data are the data or scores that are arranged in a frequency distribution. 16 Grouped Data
  • 18. The mean (also known as the arithmetic mean) is the most commonly used measure of central position. It is used to describe a set of data where the measures cluster or concentrate at a point.18 Mean
  • 20. f frequency mX classmark n sum of frequency 20 X mean mfX X n  Where:
  • 21. 21 Illustrative Example: Calculate the mean of the Mid-year Scores of Students in Mathematics. Score Frequency 41-45 1 36-40 8 31-35 8 26-30 14 21-25 7 16-20 2 Mid-year Test scores of students in Mathematics
  • 22. 22 Solution 1. Find the midpoint or class mark ( ) of each class or category. mX 2 m LL UL X   Scores 41-45 1 36-40 8 31-35 8 26-30 14 21-25 7 16-20 2
  • 23. 23 Solution 1. Find the midpoint or class mark ( ) of each class or category. mX 2 m LL UL X   Scores 41-45 1 43 36-40 8 31-35 8 26-30 14 21-25 7 16-20 2
  • 24. 24 Solution 1. Find the midpoint or class mark ( ) of each class or category. mX 2 m LL UL X   Scores 41-45 1 43 36-40 8 38 31-35 8 26-30 14 21-25 7 16-20 2
  • 25. 25 Solution 1. Find the midpoint or class mark ( ) of each class or category. mX 2 m LL UL X   Scores 41-45 1 43 36-40 8 38 31-35 8 33 26-30 14 21-25 7 16-20 2
  • 26. 26 Solution 1. Find the midpoint or class mark ( ) of each class or category. mX 2 m LL UL X   Scores 41-45 1 43 36-40 8 38 31-35 8 33 26-30 14 28 21-25 7 16-20 2
  • 27. 27 Solution 1. Find the midpoint or class mark ( ) of each class or category. mX 2 m LL UL X   Scores 41-45 1 43 36-40 8 38 31-35 8 33 26-30 14 28 21-25 7 23 16-20 2
  • 28. 28 Solution 1. Find the midpoint or class mark ( ) of each class or category. mX 2 m LL UL X   Scores 41-45 1 43 36-40 8 38 31-35 8 33 26-30 14 28 21-25 7 23 16-20 2 18
  • 29. 29 Solution 2. Multiply the frequency and the corresponding class mark . fXm Scores Frequency (f ) 41-45 1 43 36-40 8 38 31-35 8 33 26-30 14 28 21-25 7 23 16-20 2 18
  • 30. 30 Solution 2. Multiply the frequency and the corresponding class mark . fXm Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 31-35 8 33 26-30 14 28 21-25 7 23 16-20 2 18
  • 31. 31 Solution 2. Multiply the frequency and the corresponding class mark . fXm Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 26-30 14 28 21-25 7 23 16-20 2 18
  • 32. 32 Solution 2. Multiply the frequency and the corresponding class mark . fXm Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 264 26-30 14 28 21-25 7 23 16-20 2 18
  • 33. 33 Solution 2. Multiply the frequency and the corresponding class mark . fXm Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 264 26-30 14 28 392 21-25 7 23 16-20 2 18
  • 34. 34 Solution 2. Multiply the frequency and the corresponding class mark . fXm Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 264 26-30 14 28 392 21-25 7 23 161 16-20 2 18
  • 35. 35 Solution 2. Multiply the frequency and the corresponding class mark . fXm Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 264 26-30 14 28 392 21-25 7 23 161 16-20 2 18 36
  • 36. 36 Solution Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 264 26-30 14 28 392 21-25 7 23 161 16-20 2 18 36 3. Find the sum of the results in step 2. fXm
  • 37. 37 Solution 3. Find the sum of the results in step 2. Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 264 26-30 14 28 392 21-25 7 23 161 16-20 2 18 36 fXm
  • 38. Solution 4. Solve the mean using the formula. Scores Frequency (f ) 41-45 1 43 43 36-40 8 38 304 31-35 8 33 264 26-30 14 28 392 21-25 7 23 161 16-20 2 18 36 n=40 Substitution Therefore, the mean of Mid- year test is 30. mfX X n   1,200 40  30X 
  • 39. 39 Let’s practice: Find the mean weight of Grade 8 Students. Weight in kg Frequency 75-79 1 70-74 4 65-69 10 60-64 14 55-59 21 50-54 15 45-49 14 40-44 1
  • 40. Weight in kg Frequency (f) 75-79 1 70-74 4 65-69 10 60-64 14 55-59 21 50-54 15 45-49 14 40-44 1 40
  • 41. Weight in kg Frequency (f) 75-79 1 77 70-74 4 65-69 10 60-64 14 55-59 21 50-54 15 45-49 14 40-44 1 41
  • 42. Weight in kg Frequency (f) 75-79 1 77 70-74 4 72 65-69 10 60-64 14 55-59 21 50-54 15 45-49 14 40-44 1 42
  • 43. Weight in kg Frequency (f) 75-79 1 77 70-74 4 72 65-69 10 67 60-64 14 55-59 21 50-54 15 45-49 14 40-44 1 43
  • 44. Weight in kg Frequency (f) 75-79 1 77 70-74 4 72 65-69 10 67 60-64 14 62 55-59 21 50-54 15 45-49 14 40-44 1 44
  • 45. Weight in kg Frequency (f) 75-79 1 77 70-74 4 72 65-69 10 67 60-64 14 62 55-59 21 57 50-54 15 45-49 14 40-44 1 45
  • 46. Weight in kg Frequency (f) 75-79 1 77 70-74 4 72 65-69 10 67 60-64 14 62 55-59 21 57 50-54 15 52 45-49 14 40-44 1 46
  • 47. Weight in kg Frequency (f) 75-79 1 77 70-74 4 72 65-69 10 67 60-64 14 62 55-59 21 57 50-54 15 52 45-49 14 47 40-44 1 47
  • 48. Weight in kg Frequency (f) 75-79 1 77 70-74 4 72 65-69 10 67 60-64 14 62 55-59 21 57 50-54 15 52 45-49 14 47 40-44 1 42 48
  • 49. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 65-69 10 67 60-64 14 62 55-59 21 57 50-54 15 52 45-49 14 47 40-44 1 42 49
  • 50. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 60-64 14 62 55-59 21 57 50-54 15 52 45-49 14 47 40-44 1 42 50
  • 51. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 55-59 21 57 50-54 15 52 45-49 14 47 40-44 1 42 51
  • 52. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 868 55-59 21 57 50-54 15 52 45-49 14 47 40-44 1 42 52
  • 53. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 868 55-59 21 57 1197 50-54 15 52 45-49 14 47 40-44 1 42 53
  • 54. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 868 55-59 21 57 1197 50-54 15 52 780 45-49 14 47 40-44 1 42 54
  • 55. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 868 55-59 21 57 1197 50-54 15 52 780 45-49 14 47 658 40-44 1 42 55
  • 56. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 868 55-59 21 57 1197 50-54 15 52 780 45-49 14 47 658 40-44 1 42 42 56
  • 57. Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 868 55-59 21 57 1197 50-54 15 52 780 45-49 14 47 658 40-44 1 42 42 57
  • 58. Therefore, the mean weight is 57.25 Weight in kg Frequency (f) 75-79 1 77 77 70-74 4 72 288 65-69 10 67 670 60-64 14 62 868 55-59 21 57 1197 50-54 15 52 780 45-49 14 47 658 40-44 1 42 42 mfX X n   4580 80  57.25X 
  • 60. 60 Generalization The mean (also known as the arithmetic mean) is the most commonly used measure of central position. It is used to describe a set of data where the measures cluster or concentrate at a point.
  • 63. 63 Group Work CRITERIA 5 4 3 2 1 ACCURACY 100% of the steps and solutions have no mathematical errors. Almost all (90- 99%) of the steps and solutions have no mathematical errors. Almost all (85- 89%) of the steps and solutions have no mathematical errors. Most (75-84%) of the steps and solutions have no mathematical errors. Less than 75% of the steps and solutions have mathematical errors.
  • 64. 64 Group Work CRITERIA 5 4 3 2 1 ORGANIZATION It uses an appropriate and complete strategy for solving the problem. Uses clear and effective diagrams and/or tables. It uses complete strategy for solving the problem. Uses creative diagrams and/or tables. It uses strategy for solving the problem. Uses diagrams and/or tables. It uses an inappropriate strategy or application of strategy unclear. There is limited use or misuse of diagrams and/or tables. It has no particular strategy for solving the problem. It does not show use of diagrams nor tables.
  • 65. 65 Group Work CRITERIA 5 4 3 2 1 DELIVERY There is a clear and effective explanation of the solution. All steps are included so the audience does not have to infer how the task was completed. Mathematical representation is actively used as a means of communicating ideas, and precise and appropriate mathematical terminology. There is a clear explanation and appropriate use of accurate mathematical representation. There is effective use of mathematical terminology. There is explanation and mathematical representation. There is mathematical terminology There is an incomplete explanation; it is not clearly represented. There is some use of appropriate mathematical representation and terminology to the task. There is no explanation of the solutions. The explanation cannot be understood, or is unrelated to the task. There is no use or inappropriate use of mathematical representation and terminology to the task.
  • 67. 67 Assignment 1. A telecommunications company is conducting a study on the average number text messages send per day by high school students in Marikina. A random sample of 50 college students from the said area is taken. Find the mean of the data set. Class Interval Frequency 30-34 8 25-29 10 20-24 16 15-19 9 10-14 7
  • 68. 68 2. Study on Median for Grouped Data a.Describe Median. b.What is the formula in computing the median for grouped data? Reference: Mathematics Learner’s Module by Emmanuel P. Abunzo Pages 564-580
  • 69. 69