SlideShare a Scribd company logo
1 of 20
 Measures of central tendency, or “location”, attempt to
quantify what we mean when we think of as the “typical”
or “average” score in a data set.The concept is extremely
important and we encounter it frequently in daily life. For
example, we often want to know before purchasing a car
its average distance per liter of petrol. Or before accepting
a job, you might want to know what a typical salary is for
people in that position so you will know whether or not
you are going to be paid what you are worth. Or, if you are
a smoker, you might often think about how many
cigarettes you smoke “on average” per day. Statistics
geared toward measuring central tendency all focus on
this concept of “typical” or “average”.
A.To get a single value the describes the
characteristics of the entire group.
It enables one to get a bird’s eye view of the entire
data. For example, it is impossible to remember the
individual scores of students in a test. But if the
average score obtained, we get a single value to
represent the entire group.
B.To facilitate comparison
By reducing the mass of data into one single figure,
comparison between 2 groups can easily be made.
 Simple arithmetic mean (or simply mean)
 The most common measure of central tendency and
is also average.
 Its value is obtained by adding together all the values
and dividing this total by the number of items
 The mean for a finite population with N elements is
denoted by µ (Greek letter mu)
 The mean for a sample of n elements is denoted by X
 Arithmetic mean may be categorized into simple
arithmetic mean and weighted arithmetic mean.
 Formula in getting the population mean
 µ=Exi/N
Where µ is the symbol for population mean
Exi is the sum of all the values of variable X
N is the number of observations
Formula in calculating the sample mean: X=Exi/n
Or X= x1+x2+x3+…Xn/n
Where X is the symbol for sample mean
Exi is the sum of all the values of variable X
N is the number of observations
1. Add together all the values of the variable x
and obtain the total, i.e. Exi
2. Divide the total by the number of
observations, i.e N or n
Example: Calculate the average of the ff
population values:
3, 7, 5, 13, 20, 23, 39, 23,40
Solution: µ= Exi/N
 How to calculate the menu of ungrouped
data using MS excel
1. Open MS excel
2.Type or encode your data values in one
column
3. On a vacant cell, type =average(a1:a10)
4. Press Enter
 1. simple method
▪ Population Sample
Formula
µ= Exifi/N X= Exifi/N
µ is the population mean X is the sample mean
fi is the frequency fi is the frequency
xi is the midpoint of the class interval
N is the total frequency(population) (Sample)
 When a data set is arranged in ascending or
descending order, it can be divided not just in
2 parts but into various parts by different
values such as quartiles, deciles and
percentiles.These values are collectively
called quantiles or centiles and are the
extension of the median formula.
 Illustration
Lower Q Median Upper Q
Interpretation:
25% of all the data are less than or equal to Q1
50% of all the data are less than or equal to Q2 or median
75%of all the data are less than or equal to Q3
50% of all the data are lies between Q1 and Q3
 For un grouped data
3, 4, 5, 6, 6, 7, 8, 9, 9, 10 11
Find the lower and upper quartiles. Interpret the
answers.
Solutions:
Since there are 11 values, the 3rd item is Q1=5, the
middle item is Q2=7 and the 9th item is Q3=9
Now what does this mean?
 ¼ or 25% of the data has a value that is less
than or equal to 5
 ½ or 50% of the data has a value that is less
than or equal to 7
 ¾ or 75% of the data has a value that is less
than or equal 9 and
 ½ or 50% of the data lies between 5 and 9
 A decile is any of the nine values that divide
the sorted data into ten equal parts, so that
each part represents 1/10 of the sample or
population.
 Deca means ten.
D1 D2 D3 D4 D5 D6 D7 D8 D9 100%
D1 is denoted as the 1st decile under which 10% of the
total population lies.
D2 is denoted as the second decile under which 20% of
the total population lies.
D3 is denoted as the third decile under which 30% of the
total population lies.
 D1=P10;D2=P20;D3=P30 and so on. For every
one decile you multiply 10 to get the
percentile.
 The 25th percentile is also known as the 1st
quartile(Q1), the 50th percentile as the
median or 2nd Quartile (Q2) and the 75th
percentile as the 3rd Quartile (Q3)
 A percentile is any of the 99 values which divide
an ordered data set into 100 equal parts so that
each part represents 1/100 of the data set.The
word “percentile” comes from the latin word
per centum which means “per hundred”.
 Percentiles are generally used for large sets of data.
 Sometimes low percentile=good and
high percentile = good, depending on the
context.
 70th percentile for a test was 16/20. what does
this mean?
 Answer:
 Analysis: 1/20; 2/20; 5/20; 6/20; 11/20;
13/20;16/20;17/20
Smallest to Largest percentile
70% got 16/20 or less in the test
30% got more than 16/20
Here a high percentile would be considered good
since answering more questions correctly is
desirable
 Runners in a race want to finish in a time that is
less than anyone else.
low percentile is better- want a fewer people to
have that is less than yours
suppose the 20th percentile is 5.2 minutes.This
means that 20% of the people had a time that
was quicker or less than 5.2 minutes. 80% of the
people hat a time that was slower or more than
5.2 minutes.Thus, 5.2 minutes is considered as
good.
 Mary, a teacher, receives a salary that falls in
the 78% percentile.
This means that 78% of teachers has a salary
that is less than or equal to hers.
25%? Of the teachers has a salary that is more
than hers. Mary should be pleased with this
fact.

More Related Content

What's hot

3.1-3.2 Measures of Central Tendency
3.1-3.2 Measures of Central Tendency3.1-3.2 Measures of Central Tendency
3.1-3.2 Measures of Central Tendencymlong24
 
Measure of central tendency
Measure of central tendency Measure of central tendency
Measure of central tendency Kannan Iyanar
 
Lesson03_new
Lesson03_newLesson03_new
Lesson03_newshengvn
 
Kwoledge of calculation of mean,median and mode
Kwoledge of calculation of mean,median and modeKwoledge of calculation of mean,median and mode
Kwoledge of calculation of mean,median and modeAarti Vijaykumar
 
Measures of central tendency
Measures of central tendencyMeasures of central tendency
Measures of central tendencyJincy Raj
 
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 Central Tendency and Dispersion
Measures of Central Tendency and DispersionMeasures of Central Tendency and Dispersion
Measures of Central Tendency and DispersionPharmacy Universe
 
Measure OF Central Tendency
Measure OF Central TendencyMeasure OF Central Tendency
Measure OF Central TendencyIqrabutt038
 
QT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyQT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyPrithwis Mukerjee
 
Stastistics
StastisticsStastistics
StastisticsRivan001
 
Statistics in Research
Statistics in ResearchStatistics in Research
Statistics in Researchguest5477b8
 
Central tendency _dispersion
Central tendency _dispersionCentral tendency _dispersion
Central tendency _dispersionKirti Gupta
 
Lect w2 measures_of_location_and_spread
Lect w2 measures_of_location_and_spreadLect w2 measures_of_location_and_spread
Lect w2 measures_of_location_and_spreadRione Drevale
 
Measure of Central Tendency
Measure of Central TendencyMeasure of Central Tendency
Measure of Central Tendencygladysoliveros
 
Measures of central tendency
Measures of central tendencyMeasures of central tendency
Measures of central tendencyEric Silandote
 
Measure of Central Tendency (Mean, Median, Mode and Quantiles)
Measure of Central Tendency (Mean, Median, Mode and Quantiles)Measure of Central Tendency (Mean, Median, Mode and Quantiles)
Measure of Central Tendency (Mean, Median, Mode and Quantiles)Salman Khan
 

What's hot (20)

3.1-3.2 Measures of Central Tendency
3.1-3.2 Measures of Central Tendency3.1-3.2 Measures of Central Tendency
3.1-3.2 Measures of Central Tendency
 
Measure of central tendency
Measure of central tendency Measure of central tendency
Measure of central tendency
 
Lesson03_new
Lesson03_newLesson03_new
Lesson03_new
 
Kwoledge of calculation of mean,median and mode
Kwoledge of calculation of mean,median and modeKwoledge of calculation of mean,median and mode
Kwoledge of calculation of mean,median and mode
 
Measures of central tendency
Measures of central tendencyMeasures of central tendency
Measures of central tendency
 
data
datadata
data
 
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 Central Tendency and Dispersion
Measures of Central Tendency and DispersionMeasures of Central Tendency and Dispersion
Measures of Central Tendency and Dispersion
 
Measure OF Central Tendency
Measure OF Central TendencyMeasure OF Central Tendency
Measure OF Central Tendency
 
QT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyQT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central Tendency
 
Stastistics
StastisticsStastistics
Stastistics
 
Statistics in Research
Statistics in ResearchStatistics in Research
Statistics in Research
 
Central tendency _dispersion
Central tendency _dispersionCentral tendency _dispersion
Central tendency _dispersion
 
Measurement of central tendency
Measurement of central tendencyMeasurement of central tendency
Measurement of central tendency
 
Lect w2 measures_of_location_and_spread
Lect w2 measures_of_location_and_spreadLect w2 measures_of_location_and_spread
Lect w2 measures_of_location_and_spread
 
Measure of Central Tendency
Measure of Central TendencyMeasure of Central Tendency
Measure of Central Tendency
 
Measures of Spread
Measures of SpreadMeasures of Spread
Measures of Spread
 
Measures of central tendency
Measures of central tendencyMeasures of central tendency
Measures of central tendency
 
Measure of Central Tendency (Mean, Median, Mode and Quantiles)
Measure of Central Tendency (Mean, Median, Mode and Quantiles)Measure of Central Tendency (Mean, Median, Mode and Quantiles)
Measure of Central Tendency (Mean, Median, Mode and Quantiles)
 
Measure of central tendency
Measure of central tendencyMeasure of central tendency
Measure of central tendency
 

Viewers also liked

Measure of variability
Measure of variabilityMeasure of variability
Measure of variabilityHaneza Farcasa
 
Chapter 11 ,Measures of Dispersion(statistics)
Chapter  11 ,Measures of Dispersion(statistics)Chapter  11 ,Measures of Dispersion(statistics)
Chapter 11 ,Measures of Dispersion(statistics)Ananya Sharma
 
The Interpretation Of Quartiles And Percentiles July 2009
The Interpretation Of Quartiles And Percentiles   July 2009The Interpretation Of Quartiles And Percentiles   July 2009
The Interpretation Of Quartiles And Percentiles July 2009Maggie Verster
 
Standard deviation (3)
Standard deviation (3)Standard deviation (3)
Standard deviation (3)Sonali Prasad
 
Measure of dispersion part I (Range, Quartile Deviation, Interquartile devi...
Measure of dispersion part   I (Range, Quartile Deviation, Interquartile devi...Measure of dispersion part   I (Range, Quartile Deviation, Interquartile devi...
Measure of dispersion part I (Range, Quartile Deviation, Interquartile devi...Shakehand with Life
 

Viewers also liked (9)

Arithmetic sequence
Arithmetic sequenceArithmetic sequence
Arithmetic sequence
 
QUARTILES, DECILES AND PERCENTILES
QUARTILES, DECILES  AND PERCENTILESQUARTILES, DECILES  AND PERCENTILES
QUARTILES, DECILES AND PERCENTILES
 
Measure of variability
Measure of variabilityMeasure of variability
Measure of variability
 
Chapter 11 ,Measures of Dispersion(statistics)
Chapter  11 ,Measures of Dispersion(statistics)Chapter  11 ,Measures of Dispersion(statistics)
Chapter 11 ,Measures of Dispersion(statistics)
 
Quartile Deviation
Quartile DeviationQuartile Deviation
Quartile Deviation
 
The Interpretation Of Quartiles And Percentiles July 2009
The Interpretation Of Quartiles And Percentiles   July 2009The Interpretation Of Quartiles And Percentiles   July 2009
The Interpretation Of Quartiles And Percentiles July 2009
 
Standard deviation
Standard deviationStandard deviation
Standard deviation
 
Standard deviation (3)
Standard deviation (3)Standard deviation (3)
Standard deviation (3)
 
Measure of dispersion part I (Range, Quartile Deviation, Interquartile devi...
Measure of dispersion part   I (Range, Quartile Deviation, Interquartile devi...Measure of dispersion part   I (Range, Quartile Deviation, Interquartile devi...
Measure of dispersion part I (Range, Quartile Deviation, Interquartile devi...
 

Similar to just to download

polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh
polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhhpolar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh
polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhhNathanAndreiBoongali
 
Answer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docxAnswer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docxboyfieldhouse
 
QUESTION 1Question 1 Describe the purpose of ecumenical servic.docx
QUESTION 1Question 1 Describe the purpose of ecumenical servic.docxQUESTION 1Question 1 Describe the purpose of ecumenical servic.docx
QUESTION 1Question 1 Describe the purpose of ecumenical servic.docxmakdul
 
QT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyQT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyPrithwis Mukerjee
 
Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...
Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...
Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...JuliusRomano3
 
best for normal distribution.ppt
best for normal distribution.pptbest for normal distribution.ppt
best for normal distribution.pptDejeneDay
 
statical-data-1 to know how to measure.ppt
statical-data-1 to know how to measure.pptstatical-data-1 to know how to measure.ppt
statical-data-1 to know how to measure.pptNazarudinManik1
 
Module-2_Notes-with-Example for data science
Module-2_Notes-with-Example for data scienceModule-2_Notes-with-Example for data science
Module-2_Notes-with-Example for data sciencepujashri1975
 
Statistics And Correlation
Statistics And CorrelationStatistics And Correlation
Statistics And Correlationpankaj prabhakar
 
Measures of Dispersion.pptx
Measures of Dispersion.pptxMeasures of Dispersion.pptx
Measures of Dispersion.pptxVanmala Buchke
 
Week 7 a statistics
Week 7 a statisticsWeek 7 a statistics
Week 7 a statisticswawaaa789
 
CABT Math 8 measures of central tendency and dispersion
CABT Math 8   measures of central tendency and dispersionCABT Math 8   measures of central tendency and dispersion
CABT Math 8 measures of central tendency and dispersionGilbert Joseph Abueg
 
3.3 Measures of relative standing and boxplots
3.3 Measures of relative standing and boxplots3.3 Measures of relative standing and boxplots
3.3 Measures of relative standing and boxplotsLong Beach City College
 
Statistics question and answers with mcqs
Statistics question and answers with mcqsStatistics question and answers with mcqs
Statistics question and answers with mcqsNandiniYadav69
 
M.Ed Tcs 2 seminar ppt npc to submit
M.Ed Tcs 2 seminar ppt npc   to submitM.Ed Tcs 2 seminar ppt npc   to submit
M.Ed Tcs 2 seminar ppt npc to submitBINCYKMATHEW
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statisticsAiden Yeh
 
MELJUN CORTES research designing_research_methodology
MELJUN CORTES research designing_research_methodologyMELJUN CORTES research designing_research_methodology
MELJUN CORTES research designing_research_methodologyMELJUN CORTES
 

Similar to just to download (20)

polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh
polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhhpolar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh
polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh
 
Answer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docxAnswer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docx
 
QUESTION 1Question 1 Describe the purpose of ecumenical servic.docx
QUESTION 1Question 1 Describe the purpose of ecumenical servic.docxQUESTION 1Question 1 Describe the purpose of ecumenical servic.docx
QUESTION 1Question 1 Describe the purpose of ecumenical servic.docx
 
QT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central TendencyQT1 - 03 - Measures of Central Tendency
QT1 - 03 - Measures of Central Tendency
 
Statistics and probability lesson6&7
Statistics and probability lesson6&7Statistics and probability lesson6&7
Statistics and probability lesson6&7
 
Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...
Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...
Mean_Median_Mode.ppthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...
 
Chapter 11
Chapter 11Chapter 11
Chapter 11
 
best for normal distribution.ppt
best for normal distribution.pptbest for normal distribution.ppt
best for normal distribution.ppt
 
statical-data-1 to know how to measure.ppt
statical-data-1 to know how to measure.pptstatical-data-1 to know how to measure.ppt
statical-data-1 to know how to measure.ppt
 
Module-2_Notes-with-Example for data science
Module-2_Notes-with-Example for data scienceModule-2_Notes-with-Example for data science
Module-2_Notes-with-Example for data science
 
Statistics And Correlation
Statistics And CorrelationStatistics And Correlation
Statistics And Correlation
 
Measures of Dispersion.pptx
Measures of Dispersion.pptxMeasures of Dispersion.pptx
Measures of Dispersion.pptx
 
Week 7 a statistics
Week 7 a statisticsWeek 7 a statistics
Week 7 a statistics
 
CABT Math 8 measures of central tendency and dispersion
CABT Math 8   measures of central tendency and dispersionCABT Math 8   measures of central tendency and dispersion
CABT Math 8 measures of central tendency and dispersion
 
3.3 Measures of relative standing and boxplots
3.3 Measures of relative standing and boxplots3.3 Measures of relative standing and boxplots
3.3 Measures of relative standing and boxplots
 
Statistics question and answers with mcqs
Statistics question and answers with mcqsStatistics question and answers with mcqs
Statistics question and answers with mcqs
 
statistics
statisticsstatistics
statistics
 
M.Ed Tcs 2 seminar ppt npc to submit
M.Ed Tcs 2 seminar ppt npc   to submitM.Ed Tcs 2 seminar ppt npc   to submit
M.Ed Tcs 2 seminar ppt npc to submit
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
 
MELJUN CORTES research designing_research_methodology
MELJUN CORTES research designing_research_methodologyMELJUN CORTES research designing_research_methodology
MELJUN CORTES research designing_research_methodology
 

Recently uploaded

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MIND CTI
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
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
 
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot ModelNavi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot ModelDeepika Singh
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CVKhem
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
"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
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxRustici Software
 
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu SubbuApidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbuapidays
 
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
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWERMadyBayot
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDropbox
 
A Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source MilvusA Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source MilvusZilliz
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 

Recently uploaded (20)

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
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...
 
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot ModelNavi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
"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 ...
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu SubbuApidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
 
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
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
A Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source MilvusA Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source Milvus
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 

just to download

  • 1.
  • 2.  Measures of central tendency, or “location”, attempt to quantify what we mean when we think of as the “typical” or “average” score in a data set.The concept is extremely important and we encounter it frequently in daily life. For example, we often want to know before purchasing a car its average distance per liter of petrol. Or before accepting a job, you might want to know what a typical salary is for people in that position so you will know whether or not you are going to be paid what you are worth. Or, if you are a smoker, you might often think about how many cigarettes you smoke “on average” per day. Statistics geared toward measuring central tendency all focus on this concept of “typical” or “average”.
  • 3. A.To get a single value the describes the characteristics of the entire group. It enables one to get a bird’s eye view of the entire data. For example, it is impossible to remember the individual scores of students in a test. But if the average score obtained, we get a single value to represent the entire group. B.To facilitate comparison By reducing the mass of data into one single figure, comparison between 2 groups can easily be made.
  • 4.  Simple arithmetic mean (or simply mean)  The most common measure of central tendency and is also average.  Its value is obtained by adding together all the values and dividing this total by the number of items  The mean for a finite population with N elements is denoted by µ (Greek letter mu)  The mean for a sample of n elements is denoted by X  Arithmetic mean may be categorized into simple arithmetic mean and weighted arithmetic mean.
  • 5.  Formula in getting the population mean  µ=Exi/N Where µ is the symbol for population mean Exi is the sum of all the values of variable X N is the number of observations Formula in calculating the sample mean: X=Exi/n Or X= x1+x2+x3+…Xn/n Where X is the symbol for sample mean Exi is the sum of all the values of variable X N is the number of observations
  • 6. 1. Add together all the values of the variable x and obtain the total, i.e. Exi 2. Divide the total by the number of observations, i.e N or n Example: Calculate the average of the ff population values: 3, 7, 5, 13, 20, 23, 39, 23,40 Solution: µ= Exi/N
  • 7.  How to calculate the menu of ungrouped data using MS excel 1. Open MS excel 2.Type or encode your data values in one column 3. On a vacant cell, type =average(a1:a10) 4. Press Enter
  • 8.  1. simple method ▪ Population Sample Formula µ= Exifi/N X= Exifi/N µ is the population mean X is the sample mean fi is the frequency fi is the frequency xi is the midpoint of the class interval N is the total frequency(population) (Sample)
  • 9.
  • 10.  When a data set is arranged in ascending or descending order, it can be divided not just in 2 parts but into various parts by different values such as quartiles, deciles and percentiles.These values are collectively called quantiles or centiles and are the extension of the median formula.
  • 11.  Illustration Lower Q Median Upper Q Interpretation: 25% of all the data are less than or equal to Q1 50% of all the data are less than or equal to Q2 or median 75%of all the data are less than or equal to Q3 50% of all the data are lies between Q1 and Q3
  • 12.  For un grouped data 3, 4, 5, 6, 6, 7, 8, 9, 9, 10 11 Find the lower and upper quartiles. Interpret the answers. Solutions: Since there are 11 values, the 3rd item is Q1=5, the middle item is Q2=7 and the 9th item is Q3=9 Now what does this mean?
  • 13.  ¼ or 25% of the data has a value that is less than or equal to 5  ½ or 50% of the data has a value that is less than or equal to 7  ¾ or 75% of the data has a value that is less than or equal 9 and  ½ or 50% of the data lies between 5 and 9
  • 14.  A decile is any of the nine values that divide the sorted data into ten equal parts, so that each part represents 1/10 of the sample or population.  Deca means ten.
  • 15. D1 D2 D3 D4 D5 D6 D7 D8 D9 100% D1 is denoted as the 1st decile under which 10% of the total population lies. D2 is denoted as the second decile under which 20% of the total population lies. D3 is denoted as the third decile under which 30% of the total population lies.
  • 16.  D1=P10;D2=P20;D3=P30 and so on. For every one decile you multiply 10 to get the percentile.  The 25th percentile is also known as the 1st quartile(Q1), the 50th percentile as the median or 2nd Quartile (Q2) and the 75th percentile as the 3rd Quartile (Q3)
  • 17.  A percentile is any of the 99 values which divide an ordered data set into 100 equal parts so that each part represents 1/100 of the data set.The word “percentile” comes from the latin word per centum which means “per hundred”.  Percentiles are generally used for large sets of data.  Sometimes low percentile=good and high percentile = good, depending on the context.
  • 18.  70th percentile for a test was 16/20. what does this mean?  Answer:  Analysis: 1/20; 2/20; 5/20; 6/20; 11/20; 13/20;16/20;17/20 Smallest to Largest percentile 70% got 16/20 or less in the test 30% got more than 16/20 Here a high percentile would be considered good since answering more questions correctly is desirable
  • 19.  Runners in a race want to finish in a time that is less than anyone else. low percentile is better- want a fewer people to have that is less than yours suppose the 20th percentile is 5.2 minutes.This means that 20% of the people had a time that was quicker or less than 5.2 minutes. 80% of the people hat a time that was slower or more than 5.2 minutes.Thus, 5.2 minutes is considered as good.
  • 20.  Mary, a teacher, receives a salary that falls in the 78% percentile. This means that 78% of teachers has a salary that is less than or equal to hers. 25%? Of the teachers has a salary that is more than hers. Mary should be pleased with this fact.