SlideShare une entreprise Scribd logo
1  sur  21
McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.
Chapter 2
Describing Data:
Frequency Tables, Frequency
Distributions, and Graphic Presentation
2-2
GOALS
1. Organize qualitative data into a frequency table.
2. Present a frequency table as a bar chart or a pie
chart.
3. Organize quantitative data into a frequency
distribution.
4. Present a frequency distribution for quantitative
data using histograms, frequency polygons, and
cumulative frequency polygons.
2-3
Frequency Table
FREQUENCY TABLE A grouping of qualitative data into
mutually exclusive classes showing the number of
observations in each class.
2-4
Bar Charts
BAR CHART A graph in which the classes are reported on the
horizontal axis and the class frequencies on the vertical axis. The
class frequencies are proportional to the heights of the bars.
2-5
Pie Charts
PIE CHART A chart that shows the proportion or percent
that each class represents of the total number of
frequencies.
2-6
Pie Chart Using Excel
2-7
Frequency Distribution
A FrequencyFREQUENCY DISTRIBUTION A grouping of data into
mutually exclusive classes showing the number of
observations in each class.
2-8
Relative Class Frequencies
 Class frequencies can be converted to relative class
frequencies to show the fraction of the total number
of observations in each class.
 A relative frequency captures the relationship between
a class total and the total number of observations.
2-9
Frequency Distribution
Class interval: The class
interval is obtained by
subtracting the lower limit
of a class from the lower
limit of the next class.
Class frequency: The
number of observations in
each class.
Class midpoint: A point that
divides a class into two
equal parts. This is the
average of the upper and
lower class limits.
2-10
EXAMPLE – Creating a Frequency
Distribution Table
Ms. Kathryn Ball of AutoUSA
wants to develop tables, charts,
and graphs to show the typical
selling price on various dealer
lots. The table on the right
reports only the price of the 80
vehicles sold last month at
Whitner Autoplex.
2-11
Constructing a Frequency Table -
Example
 Step 1: Decide on the number of classes.
A useful recipe to determine the number of classes (k) is
the “2 to the k rule.” such that 2k
> n.
There were 80 vehicles sold. So n = 80. If we try k = 6, which
means we would use 6 classes, then 26
= 64, somewhat less than
80. Hence, 6 is not enough classes. If we let k = 7, then 27
128,
which is greater than 80. So the recommended number of classes
is 7.
 Step 2: Determine the class interval or width.
The formula is: i ≥ (H-L)/k where i is the class interval, H is
the highest observed value, L is the lowest observed value,
and k is the number of classes.
($35,925 - $15,546)/7 = $2,911
Round up to some convenient number, such as a multiple of 10
or 100. Use a class width of $3,000
2-12
Constructing a Frequency Table -
Example
 Step 3: Set the individual class limits
2-13
 Step 4: Tally the vehicle
selling prices into the
classes.
 Step 5: Count the number
of items in each class.
Constructing a Frequency Table
2-14
Relative Frequency Distribution
To convert a frequency distribution to a relative frequency
distribution, each of the class frequencies is divided by the
total number of observations.
2-15
Graphic Presentation of a Frequency
Distribution
The three commonly used graphic forms are:
 Histograms
 Frequency polygons
 Cumulative frequency distributions
2-16
Histogram
HISTOGRAM A graph in which the classes are marked on the
horizontal axis and the class frequencies on the vertical axis. The
class frequencies are represented by the heights of the bars and the
bars are drawn adjacent to each other.
2-17
Histogram Using Excel
2-18
Frequency Polygon
 A frequency polygon
also shows the shape
of a distribution and is
similar to a histogram.
 It consists of line
segments connecting
the points formed by
the intersections of the
class midpoints and the
class frequencies.
2-19
Histogram Versus Frequency Polygon
 Both provide a quick picture of the main characteristics of the
data (highs, lows, points of concentration, etc.)
 The histogram has the advantage of depicting each class as a
rectangle, with the height of the rectangular bar representing
the number in each class.
 The frequency polygon has an advantage over the histogram. It
allows us to compare directly two or more frequency
distributions.
2-20
Cumulative Frequency Distribution
2-21
Cumulative Frequency Distribution

Contenu connexe

Tendances

Data organization and presentation (statistics for research)
Data organization and presentation (statistics for research)Data organization and presentation (statistics for research)
Data organization and presentation (statistics for research)
Harve Abella
 
statistics Diagrams
 statistics Diagrams statistics Diagrams
statistics Diagrams
anil sharma
 
Further2 displaying univariate data
Further2  displaying univariate dataFurther2  displaying univariate data
Further2 displaying univariate data
kmcmullen
 
Unit 12 lesson 5 measures of variability
Unit 12 lesson 5 measures of variabilityUnit 12 lesson 5 measures of variability
Unit 12 lesson 5 measures of variability
mlabuski
 
Histograms and polygons
Histograms and polygonsHistograms and polygons
Histograms and polygons
shivang1999
 

Tendances (20)

Presentation by Ali Asghar jatoi Roll No O11 of Statistics ( Presentation of ...
Presentation by Ali Asghar jatoi Roll No O11 of Statistics ( Presentation of ...Presentation by Ali Asghar jatoi Roll No O11 of Statistics ( Presentation of ...
Presentation by Ali Asghar jatoi Roll No O11 of Statistics ( Presentation of ...
 
(Forms of presentation of data)- Economics
(Forms of presentation of data)- Economics(Forms of presentation of data)- Economics
(Forms of presentation of data)- Economics
 
Data organization and presentation (statistics for research)
Data organization and presentation (statistics for research)Data organization and presentation (statistics for research)
Data organization and presentation (statistics for research)
 
Lec 14
Lec 14Lec 14
Lec 14
 
Presentation of data ppt
Presentation of data pptPresentation of data ppt
Presentation of data ppt
 
Review formulas, functions, pivot tables, tables and charts
Review formulas, functions, pivot tables, tables and chartsReview formulas, functions, pivot tables, tables and charts
Review formulas, functions, pivot tables, tables and charts
 
Tableau - box plot
Tableau - box plotTableau - box plot
Tableau - box plot
 
Lesson 26 presenting and interpreting data in tabular and graphical froms
Lesson 26 presenting and interpreting data in tabular and graphical fromsLesson 26 presenting and interpreting data in tabular and graphical froms
Lesson 26 presenting and interpreting data in tabular and graphical froms
 
statistics Diagrams
 statistics Diagrams statistics Diagrams
statistics Diagrams
 
Further2 displaying univariate data
Further2  displaying univariate dataFurther2  displaying univariate data
Further2 displaying univariate data
 
Graphical Representation of Statistical data
Graphical Representation of Statistical dataGraphical Representation of Statistical data
Graphical Representation of Statistical data
 
Unit 12 lesson 5 measures of variability
Unit 12 lesson 5 measures of variabilityUnit 12 lesson 5 measures of variability
Unit 12 lesson 5 measures of variability
 
Diagrammatic presentation of data
Diagrammatic presentation of dataDiagrammatic presentation of data
Diagrammatic presentation of data
 
Histograms, frequency polygons, and ogives
Histograms, frequency polygons, and ogivesHistograms, frequency polygons, and ogives
Histograms, frequency polygons, and ogives
 
Presentationofdata
PresentationofdataPresentationofdata
Presentationofdata
 
DATA GRAPHICS -REPRESENTATION OF DATA
DATA GRAPHICS -REPRESENTATION OF DATADATA GRAPHICS -REPRESENTATION OF DATA
DATA GRAPHICS -REPRESENTATION OF DATA
 
Histograms and polygons
Histograms and polygonsHistograms and polygons
Histograms and polygons
 
Tabulation
Tabulation Tabulation
Tabulation
 
QT1 - 02 - Frequency Distribution
QT1 - 02 - Frequency DistributionQT1 - 02 - Frequency Distribution
QT1 - 02 - Frequency Distribution
 
Sta2023 ch02
Sta2023 ch02Sta2023 ch02
Sta2023 ch02
 

En vedette

8th pre alg -l7
8th pre alg -l78th pre alg -l7
8th pre alg -l7
jdurst65
 
Lesson 6 2 range, mean, median, mode
Lesson 6 2 range, mean, median, modeLesson 6 2 range, mean, median, mode
Lesson 6 2 range, mean, median, mode
mlabuski
 
Chapter 02
Chapter 02Chapter 02
Chapter 02
bmcfad01
 
Probability and statistics (basic statistical concepts)
Probability and statistics (basic statistical concepts)Probability and statistics (basic statistical concepts)
Probability and statistics (basic statistical concepts)
Don Bosco BSIT
 
Contextualization and-location-ntot-ap-g10
Contextualization and-location-ntot-ap-g10Contextualization and-location-ntot-ap-g10
Contextualization and-location-ntot-ap-g10
Jared Ram Juezan
 
Chapter 2: Frequency Distribution and Graphs
Chapter 2: Frequency Distribution and GraphsChapter 2: Frequency Distribution and Graphs
Chapter 2: Frequency Distribution and Graphs
Mong Mara
 
Localization & contextualization
Localization & contextualizationLocalization & contextualization
Localization & contextualization
LdPFerndz Bee
 
Introduction to statistics
Introduction to statisticsIntroduction to statistics
Introduction to statistics
akbhanj
 

En vedette (20)

Statistics
StatisticsStatistics
Statistics
 
8th pre alg -l7
8th pre alg -l78th pre alg -l7
8th pre alg -l7
 
Lesson2
Lesson2Lesson2
Lesson2
 
Math for 800 11 quadrilaterals, circles and polygons
Math for 800   11 quadrilaterals, circles and polygonsMath for 800   11 quadrilaterals, circles and polygons
Math for 800 11 quadrilaterals, circles and polygons
 
Measures of central tendency
Measures of central tendencyMeasures of central tendency
Measures of central tendency
 
Mean, median, mode
Mean, median, mode Mean, median, mode
Mean, median, mode
 
How To Find The Mean
How To Find The MeanHow To Find The Mean
How To Find The Mean
 
Lesson 6 2 range, mean, median, mode
Lesson 6 2 range, mean, median, modeLesson 6 2 range, mean, median, mode
Lesson 6 2 range, mean, median, mode
 
Chapter29
Chapter29Chapter29
Chapter29
 
Statistics and probability
Statistics and probability   Statistics and probability
Statistics and probability
 
Chapter 02
Chapter 02Chapter 02
Chapter 02
 
Basics stat ppt-types of data
Basics stat ppt-types of dataBasics stat ppt-types of data
Basics stat ppt-types of data
 
Probability and statistics (basic statistical concepts)
Probability and statistics (basic statistical concepts)Probability and statistics (basic statistical concepts)
Probability and statistics (basic statistical concepts)
 
Contextualization and-location-ntot-ap-g10
Contextualization and-location-ntot-ap-g10Contextualization and-location-ntot-ap-g10
Contextualization and-location-ntot-ap-g10
 
Chapter 2: Frequency Distribution and Graphs
Chapter 2: Frequency Distribution and GraphsChapter 2: Frequency Distribution and Graphs
Chapter 2: Frequency Distribution and Graphs
 
Lesson Plan- Measures of Central tendency of Data
Lesson Plan- Measures of Central tendency of DataLesson Plan- Measures of Central tendency of Data
Lesson Plan- Measures of Central tendency of Data
 
Localization & contextualization
Localization & contextualizationLocalization & contextualization
Localization & contextualization
 
Introduction to statistics
Introduction to statisticsIntroduction to statistics
Introduction to statistics
 
Statistics Math project class 10th
Statistics Math project class 10thStatistics Math project class 10th
Statistics Math project class 10th
 
What Is Statistics
What Is StatisticsWhat Is Statistics
What Is Statistics
 

Similaire à Chap002

Chapter 02 (1).pdf
Chapter 02 (1).pdfChapter 02 (1).pdf
Chapter 02 (1).pdf
nanifaiz
 
Statistik Chapter 2
Statistik Chapter 2Statistik Chapter 2
Statistik Chapter 2
WanBK Leo
 
Probability and statistics (frequency distributions)
Probability and statistics (frequency distributions)Probability and statistics (frequency distributions)
Probability and statistics (frequency distributions)
Don Bosco BSIT
 
Graphical presentation of data
Graphical presentation of dataGraphical presentation of data
Graphical presentation of data
prince irfan
 
Source of DATA
Source of DATASource of DATA
Source of DATA
Nahid Amin
 

Similaire à Chap002 (20)

Chap002.ppt
Chap002.pptChap002.ppt
Chap002.ppt
 
Chap002.ppt
Chap002.pptChap002.ppt
Chap002.ppt
 
Statistics slides..pptx
Statistics slides..pptxStatistics slides..pptx
Statistics slides..pptx
 
Frequency Tables, Frequency Distributions, and Graphic Presentation
Frequency Tables, Frequency Distributions, and Graphic PresentationFrequency Tables, Frequency Distributions, and Graphic Presentation
Frequency Tables, Frequency Distributions, and Graphic Presentation
 
Chapter 02 (1).pdf
Chapter 02 (1).pdfChapter 02 (1).pdf
Chapter 02 (1).pdf
 
Statistik Chapter 2
Statistik Chapter 2Statistik Chapter 2
Statistik Chapter 2
 
Frequency Distribution
Frequency DistributionFrequency Distribution
Frequency Distribution
 
Chap002
Chap002Chap002
Chap002
 
Probability and statistics (frequency distributions)
Probability and statistics (frequency distributions)Probability and statistics (frequency distributions)
Probability and statistics (frequency distributions)
 
Bab 2.ppt
Bab 2.pptBab 2.ppt
Bab 2.ppt
 
Chapter Two PPT Lecture - Part One.ppt
Chapter Two PPT Lecture - Part One.pptChapter Two PPT Lecture - Part One.ppt
Chapter Two PPT Lecture - Part One.ppt
 
Statistical graphs
Statistical graphsStatistical graphs
Statistical graphs
 
Chapter 2
Chapter 2Chapter 2
Chapter 2
 
Chapter 2
Chapter 2Chapter 2
Chapter 2
 
lesson-data-presentation-tools-1.pptx
lesson-data-presentation-tools-1.pptxlesson-data-presentation-tools-1.pptx
lesson-data-presentation-tools-1.pptx
 
Chapter Two (PART ONE).pptx
Chapter Two (PART ONE).pptxChapter Two (PART ONE).pptx
Chapter Two (PART ONE).pptx
 
Graphical presentation of data
Graphical presentation of dataGraphical presentation of data
Graphical presentation of data
 
Lecture 03.
Lecture 03.Lecture 03.
Lecture 03.
 
Displaying data
Displaying dataDisplaying data
Displaying data
 
Source of DATA
Source of DATASource of DATA
Source of DATA
 

Dernier

Dernier (20)

Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
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
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
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...
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
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...
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
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
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
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
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
 

Chap002

  • 1. McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 2 Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation
  • 2. 2-2 GOALS 1. Organize qualitative data into a frequency table. 2. Present a frequency table as a bar chart or a pie chart. 3. Organize quantitative data into a frequency distribution. 4. Present a frequency distribution for quantitative data using histograms, frequency polygons, and cumulative frequency polygons.
  • 3. 2-3 Frequency Table FREQUENCY TABLE A grouping of qualitative data into mutually exclusive classes showing the number of observations in each class.
  • 4. 2-4 Bar Charts BAR CHART A graph in which the classes are reported on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are proportional to the heights of the bars.
  • 5. 2-5 Pie Charts PIE CHART A chart that shows the proportion or percent that each class represents of the total number of frequencies.
  • 7. 2-7 Frequency Distribution A FrequencyFREQUENCY DISTRIBUTION A grouping of data into mutually exclusive classes showing the number of observations in each class.
  • 8. 2-8 Relative Class Frequencies  Class frequencies can be converted to relative class frequencies to show the fraction of the total number of observations in each class.  A relative frequency captures the relationship between a class total and the total number of observations.
  • 9. 2-9 Frequency Distribution Class interval: The class interval is obtained by subtracting the lower limit of a class from the lower limit of the next class. Class frequency: The number of observations in each class. Class midpoint: A point that divides a class into two equal parts. This is the average of the upper and lower class limits.
  • 10. 2-10 EXAMPLE – Creating a Frequency Distribution Table Ms. Kathryn Ball of AutoUSA wants to develop tables, charts, and graphs to show the typical selling price on various dealer lots. The table on the right reports only the price of the 80 vehicles sold last month at Whitner Autoplex.
  • 11. 2-11 Constructing a Frequency Table - Example  Step 1: Decide on the number of classes. A useful recipe to determine the number of classes (k) is the “2 to the k rule.” such that 2k > n. There were 80 vehicles sold. So n = 80. If we try k = 6, which means we would use 6 classes, then 26 = 64, somewhat less than 80. Hence, 6 is not enough classes. If we let k = 7, then 27 128, which is greater than 80. So the recommended number of classes is 7.  Step 2: Determine the class interval or width. The formula is: i ≥ (H-L)/k where i is the class interval, H is the highest observed value, L is the lowest observed value, and k is the number of classes. ($35,925 - $15,546)/7 = $2,911 Round up to some convenient number, such as a multiple of 10 or 100. Use a class width of $3,000
  • 12. 2-12 Constructing a Frequency Table - Example  Step 3: Set the individual class limits
  • 13. 2-13  Step 4: Tally the vehicle selling prices into the classes.  Step 5: Count the number of items in each class. Constructing a Frequency Table
  • 14. 2-14 Relative Frequency Distribution To convert a frequency distribution to a relative frequency distribution, each of the class frequencies is divided by the total number of observations.
  • 15. 2-15 Graphic Presentation of a Frequency Distribution The three commonly used graphic forms are:  Histograms  Frequency polygons  Cumulative frequency distributions
  • 16. 2-16 Histogram HISTOGRAM A graph in which the classes are marked on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are represented by the heights of the bars and the bars are drawn adjacent to each other.
  • 18. 2-18 Frequency Polygon  A frequency polygon also shows the shape of a distribution and is similar to a histogram.  It consists of line segments connecting the points formed by the intersections of the class midpoints and the class frequencies.
  • 19. 2-19 Histogram Versus Frequency Polygon  Both provide a quick picture of the main characteristics of the data (highs, lows, points of concentration, etc.)  The histogram has the advantage of depicting each class as a rectangle, with the height of the rectangular bar representing the number in each class.  The frequency polygon has an advantage over the histogram. It allows us to compare directly two or more frequency distributions.