尊敬的 微信汇率：1円 ≈ 0.046166 元 支付宝汇率：1円 ≈ 0.046257元 [退出登录]
SlideShare a Scribd company logo

Lesson02_Static.11

•Download as PPT, PDF•
•
T
thangv

This document summarizes techniques for organizing and presenting numerical and categorical data in tables and charts. It covers organizing numerical data using ordered arrays and stem-and-leaf displays. It also discusses tabulating and graphing numerical data using frequency distributions, histograms, polygons, and cumulative distributions tables and ogives. For categorical data, it describes organizing univariate data with summary tables and graphing it with bar charts, pie charts, and Pareto diagrams. It also addresses tabulating bivariate categorical data with contingency tables and side-by-side charts. Finally, it discusses principles of graphical excellence and common errors to avoid in data presentation.

Technology
1 of 28
Statistics for Management Presenting Data in Tables and Charts
Lesson Topics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
2 144677 3 028 4 1 1. Organizing Numerical Data Numerical Data Ordered Array Stem and Leaf Display Frequency Distributions Cumulative Distributions Histograms Polygons Ogive Tables 41, 24, 32, 26, 27, 27, 30, 24, 38, 21 21, 24, 24, 26, 27, 27, 30, 32, 38, 41
2 1 4 4 6 7 7 Organizing Numerical Data: ,[object Object],[object Object],[object Object],[object Object],[object Object],3 0 2 8 4 1
2 144677 3 028 4 1 Organizing Numerical Data Numerical Data Ordered Array Stem and Leaf Display Histograms Ogive Tables 41, 24, 32, 26, 27, 27, 30, 24, 38, 21 21, 24, 24, 26, 27, 27, 30, 32, 38, 41 Frequency Distributions Cumulative Distributions Polygons
2.Tabulating Numerical Data: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tabulating Numerical Data: Frequency Distributions Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Frequency 10 but under 20 3 .15 15 20 but under 30 6 .30 30 30 but under 40 5 .25 25 40 but under 50 4 .20 20 50 but under 60 2 .10 10 Total 20 1 100 Relative Frequency Percentage
Graphing Numerical Data: The Histogram Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Midpoints No Gaps Between Bars
Graphing Numerical Data: The Frequency Polygon Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Midpoints
Cumulative Cumulative Class Frequency % Frequency 10 but under 20 3 15 20 but under 30 9 45 30 but under 40 14 70 40 but under 50 18 90 50 but under 60 20 100 Tabulating Numerical Data: Cumulative Frequency Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58
Graphing Numerical Data: The Ogive (Cumulative % Polygon) Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Boundaries
3.Organizing Categorical Data Univariate Data: Categorical Data Tabulating Data The Summary Table Graphing Data Pie Charts Pareto Diagram Bar Charts
Summary Table (for an investor’s portfolio) Investment Category Amount Percentage (in thousands $) Stocks 46.5 42.27 Bonds 32 29.09 CD 15.5 14.09 Savings 16 14.55 Total 110 100 Variables are Categorical.
4.Organizing Categorical Data Univariate Data: Categorical Data Tabulating Data The Summary Table Graphing Data Pie Charts Pareto Diagram Bar Charts
Bar Chart (for an investor’s portfolio)
Pie Chart (for an investor’s portfolio) Percentages are rounded to the nearest percent. Amount Invested in K$ Savings 15% CD 14% Bonds 29% Stocks 42%
Pareto Diagram Axis for bar chart shows % invested in each category. Axis for line graph shows cumulative % invested .
5. Organizing Bivariate Categorical Data ,[object Object],[object Object]
Organizing Categorical Data Bivariate Data: Contingency Table: Investment in Thousands of Dollars Investment Investor A Investor B Investor C Total Category Stocks 46.5 55 27.5 129 Bonds 32 44 19 95 CD 15.5 20 13.5 49 Savings 16 28 7 51 Total 110 147 67 324
Organizing Categorical Data Bivariate Data: Side by Side Chart
Principals of Graphical excellence ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],Errors in Presenting Data
‘ Chart Junk’ Good Presentation 1960: $1.00 1970: $1.60 1980: $3.10 1990: $3.80 Minimum Wage Minimum Wage 0 2 4 1960 1970 1980 1990 $ Bad Presentation 
No Relative Basis Good Presentation A’s received by students. A’s received by students. Bad Presentation 0  200 300 FR SO JR SR Freq.  10%  30% FR SO JR SR % FR = Freshmen, SO = Sophomore, JR = Junior, SR = Senior 
Compressing Vertical Axis Good Presentation Quarterly Sales Quarterly Sales Bad Presentation 0 25 50 Q1 Q2 Q3 Q4 $ 0 100 200 Q1 Q2 Q3 Q4 $ 
No Zero Point on Vertical Axis Good Presentation Monthly Sales Monthly Sales Bad Presentation 0 39 42 45 J F M A M J $ 36 39 42 45 J F M A M J $ Graphing the first six months of sales. 36 
No Zero Point on Vertical Axis Good Presentation Monthly Sales Monthly Sales Bad Presentation 0 20 40 60 J F M A M J $ 36 39 42 45 J F M A M J $ Graphing the first six months of sales. 
Lesson Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Recommended

Lesson02_new
Lesson02_newLesson02_new
Lesson02_new
shengvn
 
Lecture 10.1 10.2 bt
Lecture 10.1 10.2 btLecture 10.1 10.2 bt
Lecture 10.1 10.2 bt
btmathematics
 
Lecture 10.1 10.2 bt
Lecture 10.1 10.2 btLecture 10.1 10.2 bt
Lecture 10.1 10.2 bt
btmathematics
 
Basic Stat Notes
Basic Stat NotesBasic Stat Notes
Basic Stat Notes
roopcool
 
Graphs, charts, and tables ppt @ bec doms
Graphs, charts, and tables ppt @ bec domsGraphs, charts, and tables ppt @ bec doms
Graphs, charts, and tables ppt @ bec doms
Babasab Patil
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
University of Jaffna
 
Displaying data
Displaying dataDisplaying data
Displaying data
AbhishekDas15
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
Sr Edith Bogue
 

Recommended

Lesson02_new
Lesson02_newLesson02_new
Lesson02_new
shengvn
 
Lecture 10.1 10.2 bt
Lecture 10.1 10.2 btLecture 10.1 10.2 bt
Lecture 10.1 10.2 bt
btmathematics
 
Lecture 10.1 10.2 bt
Lecture 10.1 10.2 btLecture 10.1 10.2 bt
Lecture 10.1 10.2 bt
btmathematics
 
Basic Stat Notes
Basic Stat NotesBasic Stat Notes
Basic Stat Notes
roopcool
 
Graphs, charts, and tables ppt @ bec doms
Graphs, charts, and tables ppt @ bec domsGraphs, charts, and tables ppt @ bec doms
Graphs, charts, and tables ppt @ bec doms
Babasab Patil
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
University of Jaffna
 
Displaying data
Displaying dataDisplaying data
Displaying data
AbhishekDas15
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
Sr Edith Bogue
 
Biostatistics Frequency distribution
Biostatistics Frequency distributionBiostatistics Frequency distribution
Biostatistics Frequency distribution
HARINATHA REDDY ASWARTHA
 
2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives
mlong24
 
Statistik Chapter 2
Statistik Chapter 2Statistik Chapter 2
Statistik Chapter 2
WanBK Leo
 
Descrptive statistics
Descrptive statisticsDescrptive statistics
Descrptive statistics
DrZahid Khan
 
Data Handling
Data HandlingData Handling
Data Handling
Narmada Valley International School
 
03.data presentation(2015) 2
03.data presentation(2015) 203.data presentation(2015) 2
03.data presentation(2015) 2
Mmedsc Hahm
 
Understanding data through presentation_contd
Understanding data through presentation_contdUnderstanding data through presentation_contd
Understanding data through presentation_contd
Southern Range, Berhampur, Odisha
 
Methods of data presention
Methods of data presentionMethods of data presention
Methods of data presention
Dr Vaibhav Gupta
 
Tabular and Graphical Representation of Data
Tabular and Graphical Representation of Data Tabular and Graphical Representation of Data
Tabular and Graphical Representation of Data
Sir Parashurambhau College, Pune
 
Source of DATA
Source of DATASource of DATA
Source of DATA
Nahid Amin
 
Presentationofdata
PresentationofdataPresentationofdata
Presentationofdata
abhaypratap pandey
 
Aed1222 lesson 6 2nd part
Aed1222 lesson 6 2nd partAed1222 lesson 6 2nd part
Aed1222 lesson 6 2nd part
nurun2010
 
An Introduction to Statistics
An Introduction to StatisticsAn Introduction to Statistics
An Introduction to Statistics
Nazrul Islam
 
Data presentation
Data presentationData presentation
Data presentation
MaiBabes17
 
[Tema 1] estadística descriptiva
[Tema 1] estadística descriptiva[Tema 1] estadística descriptiva
[Tema 1] estadística descriptiva
7158AS
 
Ogive slide share
Ogive slide shareOgive slide share
Ogive slide share
SreejayaPV
 
Data organization
Data organizationData organization
Data organization
rowell balala
 
Presentation of data
Presentation of dataPresentation of data
Presentation of data
Winona Esel Bernardo
 
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
 
Presentation of data mod 6
Presentation of data mod 6Presentation of data mod 6
Presentation of data mod 6
Winona Esel Bernardo
 
Lecture 1 - Overview.pptx
Lecture 1 - Overview.pptxLecture 1 - Overview.pptx
Lecture 1 - Overview.pptx
DrAnisFatima
 
lecture 4 Graphs.pptx
lecture 4 Graphs.pptxlecture 4 Graphs.pptx
lecture 4 Graphs.pptx
ssuser378d7c
 

More Related Content

What's hot

Biostatistics Frequency distribution
Biostatistics Frequency distributionBiostatistics Frequency distribution
Biostatistics Frequency distribution
HARINATHA REDDY ASWARTHA
 
2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives
mlong24
 
Statistik Chapter 2
Statistik Chapter 2Statistik Chapter 2
Statistik Chapter 2
WanBK Leo
 
Descrptive statistics
Descrptive statisticsDescrptive statistics
Descrptive statistics
DrZahid Khan
 
Data Handling
Data HandlingData Handling
Data Handling
Narmada Valley International School
 
03.data presentation(2015) 2
03.data presentation(2015) 203.data presentation(2015) 2
03.data presentation(2015) 2
Mmedsc Hahm
 
Understanding data through presentation_contd
Understanding data through presentation_contdUnderstanding data through presentation_contd
Understanding data through presentation_contd
Southern Range, Berhampur, Odisha
 
Methods of data presention
Methods of data presentionMethods of data presention
Methods of data presention
Dr Vaibhav Gupta
 
Tabular and Graphical Representation of Data
Tabular and Graphical Representation of Data Tabular and Graphical Representation of Data
Tabular and Graphical Representation of Data
Sir Parashurambhau College, Pune
 
Source of DATA
Source of DATASource of DATA
Source of DATA
Nahid Amin
 
Presentationofdata
PresentationofdataPresentationofdata
Presentationofdata
abhaypratap pandey
 
Aed1222 lesson 6 2nd part
Aed1222 lesson 6 2nd partAed1222 lesson 6 2nd part
Aed1222 lesson 6 2nd part
nurun2010
 
An Introduction to Statistics
An Introduction to StatisticsAn Introduction to Statistics
An Introduction to Statistics
Nazrul Islam
 
Data presentation
Data presentationData presentation
Data presentation
MaiBabes17
 
[Tema 1] estadística descriptiva
[Tema 1] estadística descriptiva[Tema 1] estadística descriptiva
[Tema 1] estadística descriptiva
7158AS
 
Ogive slide share
Ogive slide shareOgive slide share
Ogive slide share
SreejayaPV
 
Data organization
Data organizationData organization
Data organization
rowell balala
 
Presentation of data
Presentation of dataPresentation of data
Presentation of data
Winona Esel Bernardo
 
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
 
Presentation of data mod 6
Presentation of data mod 6Presentation of data mod 6
Presentation of data mod 6
Winona Esel Bernardo
 

What's hot (20)

Biostatistics Frequency distribution
Biostatistics Frequency distributionBiostatistics Frequency distribution
Biostatistics Frequency distribution
 
2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives2.3 Histogram/Frequency Polygon/Ogives
2.3 Histogram/Frequency Polygon/Ogives
 
Statistik Chapter 2
Statistik Chapter 2Statistik Chapter 2
Statistik Chapter 2
 
Descrptive statistics
Descrptive statisticsDescrptive statistics
Descrptive statistics
 
Data Handling
Data HandlingData Handling
Data Handling
 
03.data presentation(2015) 2
03.data presentation(2015) 203.data presentation(2015) 2
03.data presentation(2015) 2
 
Understanding data through presentation_contd
Understanding data through presentation_contdUnderstanding data through presentation_contd
Understanding data through presentation_contd
 
Methods of data presention
Methods of data presentionMethods of data presention
Methods of data presention
 
Tabular and Graphical Representation of Data
Tabular and Graphical Representation of Data Tabular and Graphical Representation of Data
Tabular and Graphical Representation of Data
 
Source of DATA
Source of DATASource of DATA
Source of DATA
 
Presentationofdata
PresentationofdataPresentationofdata
Presentationofdata
 
Aed1222 lesson 6 2nd part
Aed1222 lesson 6 2nd partAed1222 lesson 6 2nd part
Aed1222 lesson 6 2nd part
 
An Introduction to Statistics
An Introduction to StatisticsAn Introduction to Statistics
An Introduction to Statistics
 
Data presentation
Data presentationData presentation
Data presentation
 
[Tema 1] estadística descriptiva
[Tema 1] estadística descriptiva[Tema 1] estadística descriptiva
[Tema 1] estadística descriptiva
 
Ogive slide share
Ogive slide shareOgive slide share
Ogive slide share
 
Data organization
Data organizationData organization
Data organization
 
Presentation of data
Presentation of dataPresentation of data
Presentation of data
 
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)
 
Presentation of data mod 6
Presentation of data mod 6Presentation of data mod 6
Presentation of data mod 6
 

Similar to Lesson02_Static.11

Lecture 1 - Overview.pptx
Lecture 1 - Overview.pptxLecture 1 - Overview.pptx
Lecture 1 - Overview.pptx
DrAnisFatima
 
lecture 4 Graphs.pptx
lecture 4 Graphs.pptxlecture 4 Graphs.pptx
lecture 4 Graphs.pptx
ssuser378d7c
 
Ee184405 statistika dan stokastik statistik deskriptif 1 grafik
Ee184405 statistika dan stokastik statistik deskriptif 1 grafikEe184405 statistika dan stokastik statistik deskriptif 1 grafik
Ee184405 statistika dan stokastik statistik deskriptif 1 grafik
yusufbf
 
Business Statistics Chapter 2
Business Statistics Chapter 2Business Statistics Chapter 2
Business Statistics Chapter 2
Lux PP
 
Numerical and statistical methods new
Numerical and statistical methods newNumerical and statistical methods new
Numerical and statistical methods new
Aabha Tiwari
 
Newbold_chap02.ppt
Newbold_chap02.pptNewbold_chap02.ppt
Newbold_chap02.ppt
cfisicaster
 
Data collection and presentation
Data collection and presentationData collection and presentation
Data collection and presentation
ferdaus44
 
Taxonomy of charts
Taxonomy of chartsTaxonomy of charts
Taxonomy of charts
Ritvvij Parrikh
 
Charts and graphs
Charts and graphsCharts and graphs
Charts and graphs
ScholarsPoint1
 
2.3 Graphs that enlighten and graphs that deceive
2.3 Graphs that enlighten and graphs that deceive2.3 Graphs that enlighten and graphs that deceive
2.3 Graphs that enlighten and graphs that deceive
Long Beach City College
 
Bbs11 ppt ch02
Bbs11 ppt ch02Bbs11 ppt ch02
Bbs11 ppt ch02
Tuul Tuul
 
Basic business statistics 2
Basic business statistics 2Basic business statistics 2
Basic business statistics 2
Anwar Afridi
 
Intro to quant_analysis_students
Intro to quant_analysis_studentsIntro to quant_analysis_students
Intro to quant_analysis_students
mstegman
 
Chapter3
Chapter3Chapter3
Chapter3
Richard Ferreria
 
2 Lecture 2 organizing and displaying of data.pptx
2 Lecture 2 organizing and displaying of data.pptx2 Lecture 2 organizing and displaying of data.pptx
2 Lecture 2 organizing and displaying of data.pptx
SadaAlak1
 
Pre_processing_the_data_using_advance_technique
Pre_processing_the_data_using_advance_techniquePre_processing_the_data_using_advance_technique
Pre_processing_the_data_using_advance_technique
Bhushan134837
 
Presenting Data in Tables and Charts
Presenting Data in Tables and ChartsPresenting Data in Tables and Charts
Presenting Data in Tables and Charts
Yesica Adicondro
 
Stats chapter 1
Stats chapter 1Stats chapter 1
Stats chapter 1
Richard Ferreria
 
Tps4e ch1 1.1
Tps4e ch1 1.1Tps4e ch1 1.1
Tps4e ch1 1.1
Thomas Lee
 
Presentation of Data
Presentation of DataPresentation of Data
Presentation of Data
Umair Anwar
 

Similar to Lesson02_Static.11 (20)

Lecture 1 - Overview.pptx
Lecture 1 - Overview.pptxLecture 1 - Overview.pptx
Lecture 1 - Overview.pptx
 
lecture 4 Graphs.pptx
lecture 4 Graphs.pptxlecture 4 Graphs.pptx
lecture 4 Graphs.pptx
 
Ee184405 statistika dan stokastik statistik deskriptif 1 grafik
Ee184405 statistika dan stokastik statistik deskriptif 1 grafikEe184405 statistika dan stokastik statistik deskriptif 1 grafik
Ee184405 statistika dan stokastik statistik deskriptif 1 grafik
 
Business Statistics Chapter 2
Business Statistics Chapter 2Business Statistics Chapter 2
Business Statistics Chapter 2
 
Numerical and statistical methods new
Numerical and statistical methods newNumerical and statistical methods new
Numerical and statistical methods new
 
Newbold_chap02.ppt
Newbold_chap02.pptNewbold_chap02.ppt
Newbold_chap02.ppt
 
Data collection and presentation
Data collection and presentationData collection and presentation
Data collection and presentation
 
Taxonomy of charts
Taxonomy of chartsTaxonomy of charts
Taxonomy of charts
 
Charts and graphs
Charts and graphsCharts and graphs
Charts and graphs
 
2.3 Graphs that enlighten and graphs that deceive
2.3 Graphs that enlighten and graphs that deceive2.3 Graphs that enlighten and graphs that deceive
2.3 Graphs that enlighten and graphs that deceive
 
Bbs11 ppt ch02
Bbs11 ppt ch02Bbs11 ppt ch02
Bbs11 ppt ch02
 
Basic business statistics 2
Basic business statistics 2Basic business statistics 2
Basic business statistics 2
 
Intro to quant_analysis_students
Intro to quant_analysis_studentsIntro to quant_analysis_students
Intro to quant_analysis_students
 
Chapter3
Chapter3Chapter3
Chapter3
 
2 Lecture 2 organizing and displaying of data.pptx
2 Lecture 2 organizing and displaying of data.pptx2 Lecture 2 organizing and displaying of data.pptx
2 Lecture 2 organizing and displaying of data.pptx
 
Pre_processing_the_data_using_advance_technique
Pre_processing_the_data_using_advance_techniquePre_processing_the_data_using_advance_technique
Pre_processing_the_data_using_advance_technique
 
Presenting Data in Tables and Charts
Presenting Data in Tables and ChartsPresenting Data in Tables and Charts
Presenting Data in Tables and Charts
 
Stats chapter 1
Stats chapter 1Stats chapter 1
Stats chapter 1
 
Tps4e ch1 1.1
Tps4e ch1 1.1Tps4e ch1 1.1
Tps4e ch1 1.1
 
Presentation of Data
Presentation of DataPresentation of Data
Presentation of Data
 

More from thangv

Session 7_OM
Session 7_OMSession 7_OM
Session 7_OM
thangv
 
Session 6
Session 6Session 6
Session 6
thangv
 
Session 2
Session 2Session 2
Session 2
thangv
 
Session 4_OM
Session 4_OMSession 4_OM
Session 4_OM
thangv
 
Session 5
Session 5Session 5
Session 5
thangv
 
Session 3
Session 3Session 3
Session 3
thangv
 
Session 8
Session 8Session 8
Session 8
thangv
 
Session 1
Session 1Session 1
Session 1
thangv
 
Chapter 7_OM
Chapter 7_OMChapter 7_OM
Chapter 7_OM
thangv
 
Chapter 7_OM
Chapter 7_OMChapter 7_OM
Chapter 7_OMthangv
 
Session 1_OM
Session 1_OMSession 1_OM
Session 1_OM
thangv
 
Session 8_OM
Session 8_OMSession 8_OM
Session 8_OM
thangv
 
Lesson03_static11
Lesson03_static11Lesson03_static11
Lesson03_static11
thangv
 
Lesson06_static11
Lesson06_static11Lesson06_static11
Lesson06_static11
thangv
 
Lesson05_Static11
Lesson05_Static11Lesson05_Static11
Lesson05_Static11
thangv
 
Lesson04_Static11
Lesson04_Static11Lesson04_Static11
Lesson04_Static11
thangv
 
Lesson08_static11
Lesson08_static11Lesson08_static11
Lesson08_static11
thangv
 
Lesson01_Static.11
Lesson01_Static.11Lesson01_Static.11
Lesson01_Static.11
thangv
 

More from thangv (18)

Session 7_OM
Session 7_OMSession 7_OM
Session 7_OM
 
Session 6
Session 6Session 6
Session 6
 
Session 2
Session 2Session 2
Session 2
 
Session 4_OM
Session 4_OMSession 4_OM
Session 4_OM
 
Session 5
Session 5Session 5
Session 5
 
Session 3
Session 3Session 3
Session 3
 
Session 8
Session 8Session 8
Session 8
 
Session 1
Session 1Session 1
Session 1
 
Chapter 7_OM
Chapter 7_OMChapter 7_OM
Chapter 7_OM
 
Chapter 7_OM
Chapter 7_OMChapter 7_OM
Chapter 7_OM
 
Session 1_OM
Session 1_OMSession 1_OM
Session 1_OM
 
Session 8_OM
Session 8_OMSession 8_OM
Session 8_OM
 
Lesson03_static11
Lesson03_static11Lesson03_static11
Lesson03_static11
 
Lesson06_static11
Lesson06_static11Lesson06_static11
Lesson06_static11
 
Lesson05_Static11
Lesson05_Static11Lesson05_Static11
Lesson05_Static11
 
Lesson04_Static11
Lesson04_Static11Lesson04_Static11
Lesson04_Static11
 
Lesson08_static11
Lesson08_static11Lesson08_static11
Lesson08_static11
 
Lesson01_Static.11
Lesson01_Static.11Lesson01_Static.11
Lesson01_Static.11
 

Recently uploaded

MongoDB vs ScyllaDB: Tractian’s Experience with Real-Time ML
MongoDB vs ScyllaDB: Tractian’s Experience with Real-Time MLMongoDB vs ScyllaDB: Tractian’s Experience with Real-Time ML
MongoDB vs ScyllaDB: Tractian’s Experience with Real-Time ML
ScyllaDB
 
Facilitation Skills - When to Use and Why.pptx
Facilitation Skills - When to Use and Why.pptxFacilitation Skills - When to Use and Why.pptx
Facilitation Skills - When to Use and Why.pptx
Knoldus Inc.
 
TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...
TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...
TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...
TrustArc
 
Day 4 - Excel Automation and Data Manipulation
Day 4 - Excel Automation and Data ManipulationDay 4 - Excel Automation and Data Manipulation
Day 4 - Excel Automation and Data Manipulation
UiPathCommunity
 
ScyllaDB Real-Time Event Processing with CDC
ScyllaDB Real-Time Event Processing with CDCScyllaDB Real-Time Event Processing with CDC
ScyllaDB Real-Time Event Processing with CDC
ScyllaDB
 
Containers & AI - Beauty and the Beast!?!
Containers & AI - Beauty and the Beast!?!Containers & AI - Beauty and the Beast!?!
Containers & AI - Beauty and the Beast!?!
Tobias Schneck
 
CNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My Identity
CNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My IdentityCNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My Identity
CNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My Identity
Cynthia Thomas
 
ThousandEyes New Product Features and Release Highlights: June 2024
ThousandEyes New Product Features and Release Highlights: June 2024ThousandEyes New Product Features and Release Highlights: June 2024
ThousandEyes New Product Features and Release Highlights: June 2024
ThousandEyes
 
Mutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented ChatbotsMutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented Chatbots
Pablo Gómez Abajo
 
Poznań ACE event - 19.06.2024 Team 24 Wrapup slidedeck
Poznań ACE event - 19.06.2024 Team 24 Wrapup slidedeckPoznań ACE event - 19.06.2024 Team 24 Wrapup slidedeck
Poznań ACE event - 19.06.2024 Team 24 Wrapup slidedeck
FilipTomaszewski5
 
Discover the Unseen: Tailored Recommendation of Unwatched Content
Discover the Unseen: Tailored Recommendation of Unwatched ContentDiscover the Unseen: Tailored Recommendation of Unwatched Content
Discover the Unseen: Tailored Recommendation of Unwatched Content
ScyllaDB
 
Demystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through StorytellingDemystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through Storytelling
Enterprise Knowledge
 
MongoDB to ScyllaDB: Technical Comparison and the Path to Success
MongoDB to ScyllaDB: Technical Comparison and the Path to SuccessMongoDB to ScyllaDB: Technical Comparison and the Path to Success
MongoDB to ScyllaDB: Technical Comparison and the Path to Success
ScyllaDB
 
Guidelines for Effective Data Visualization
Guidelines for Effective Data VisualizationGuidelines for Effective Data Visualization
Guidelines for Effective Data Visualization
UmmeSalmaM1
 
Building a Semantic Layer of your Data Platform
Building a Semantic Layer of your Data PlatformBuilding a Semantic Layer of your Data Platform
Building a Semantic Layer of your Data Platform
Enterprise Knowledge
 
Radically Outperforming DynamoDB @ Digital Turbine with SADA and Google Cloud
Radically Outperforming DynamoDB @ Digital Turbine with SADA and Google CloudRadically Outperforming DynamoDB @ Digital Turbine with SADA and Google Cloud
Radically Outperforming DynamoDB @ Digital Turbine with SADA and Google Cloud
ScyllaDB
 
APJC Introduction to ThousandEyes Webinar
APJC Introduction to ThousandEyes WebinarAPJC Introduction to ThousandEyes Webinar
APJC Introduction to ThousandEyes Webinar
ThousandEyes
 
Multivendor cloud production with VSF TR-11 - there and back again
Multivendor cloud production with VSF TR-11 - there and back againMultivendor cloud production with VSF TR-11 - there and back again
Multivendor cloud production with VSF TR-11 - there and back again
Kieran Kunhya
 
DynamoDB to ScyllaDB: Technical Comparison and the Path to Success
DynamoDB to ScyllaDB: Technical Comparison and the Path to SuccessDynamoDB to ScyllaDB: Technical Comparison and the Path to Success
DynamoDB to ScyllaDB: Technical Comparison and the Path to Success
ScyllaDB
 
ScyllaDB Tablets: Rethinking Replication
ScyllaDB Tablets: Rethinking ReplicationScyllaDB Tablets: Rethinking Replication
ScyllaDB Tablets: Rethinking Replication
ScyllaDB
 

Recently uploaded (20)

MongoDB vs ScyllaDB: Tractian’s Experience with Real-Time ML
MongoDB vs ScyllaDB: Tractian’s Experience with Real-Time MLMongoDB vs ScyllaDB: Tractian’s Experience with Real-Time ML
MongoDB vs ScyllaDB: Tractian’s Experience with Real-Time ML
 
Facilitation Skills - When to Use and Why.pptx
Facilitation Skills - When to Use and Why.pptxFacilitation Skills - When to Use and Why.pptx
Facilitation Skills - When to Use and Why.pptx
 
TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...
TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...
TrustArc Webinar - Your Guide for Smooth Cross-Border Data Transfers and Glob...
 
Day 4 - Excel Automation and Data Manipulation
Day 4 - Excel Automation and Data ManipulationDay 4 - Excel Automation and Data Manipulation
Day 4 - Excel Automation and Data Manipulation
 
ScyllaDB Real-Time Event Processing with CDC
ScyllaDB Real-Time Event Processing with CDCScyllaDB Real-Time Event Processing with CDC
ScyllaDB Real-Time Event Processing with CDC
 
Containers & AI - Beauty and the Beast!?!
Containers & AI - Beauty and the Beast!?!Containers & AI - Beauty and the Beast!?!
Containers & AI - Beauty and the Beast!?!
 
CNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My Identity
CNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My IdentityCNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My Identity
CNSCon 2024 Lightning Talk: Don’t Make Me Impersonate My Identity
 
ThousandEyes New Product Features and Release Highlights: June 2024
ThousandEyes New Product Features and Release Highlights: June 2024ThousandEyes New Product Features and Release Highlights: June 2024
ThousandEyes New Product Features and Release Highlights: June 2024
 
Mutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented ChatbotsMutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented Chatbots
 
Poznań ACE event - 19.06.2024 Team 24 Wrapup slidedeck
Poznań ACE event - 19.06.2024 Team 24 Wrapup slidedeckPoznań ACE event - 19.06.2024 Team 24 Wrapup slidedeck
Poznań ACE event - 19.06.2024 Team 24 Wrapup slidedeck
 
Discover the Unseen: Tailored Recommendation of Unwatched Content
Discover the Unseen: Tailored Recommendation of Unwatched ContentDiscover the Unseen: Tailored Recommendation of Unwatched Content
Discover the Unseen: Tailored Recommendation of Unwatched Content
 
Demystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through StorytellingDemystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through Storytelling
 
MongoDB to ScyllaDB: Technical Comparison and the Path to Success
MongoDB to ScyllaDB: Technical Comparison and the Path to SuccessMongoDB to ScyllaDB: Technical Comparison and the Path to Success
MongoDB to ScyllaDB: Technical Comparison and the Path to Success
 
Guidelines for Effective Data Visualization
Guidelines for Effective Data VisualizationGuidelines for Effective Data Visualization
Guidelines for Effective Data Visualization
 
Building a Semantic Layer of your Data Platform
Building a Semantic Layer of your Data PlatformBuilding a Semantic Layer of your Data Platform
Building a Semantic Layer of your Data Platform
 
Radically Outperforming DynamoDB @ Digital Turbine with SADA and Google Cloud
Radically Outperforming DynamoDB @ Digital Turbine with SADA and Google CloudRadically Outperforming DynamoDB @ Digital Turbine with SADA and Google Cloud
Radically Outperforming DynamoDB @ Digital Turbine with SADA and Google Cloud
 
APJC Introduction to ThousandEyes Webinar
APJC Introduction to ThousandEyes WebinarAPJC Introduction to ThousandEyes Webinar
APJC Introduction to ThousandEyes Webinar
 
Multivendor cloud production with VSF TR-11 - there and back again
Multivendor cloud production with VSF TR-11 - there and back againMultivendor cloud production with VSF TR-11 - there and back again
Multivendor cloud production with VSF TR-11 - there and back again
 
DynamoDB to ScyllaDB: Technical Comparison and the Path to Success
DynamoDB to ScyllaDB: Technical Comparison and the Path to SuccessDynamoDB to ScyllaDB: Technical Comparison and the Path to Success
DynamoDB to ScyllaDB: Technical Comparison and the Path to Success
 
ScyllaDB Tablets: Rethinking Replication
ScyllaDB Tablets: Rethinking ReplicationScyllaDB Tablets: Rethinking Replication
ScyllaDB Tablets: Rethinking Replication
 

Lesson02_Static.11

  • 1. Statistics for Management Presenting Data in Tables and Charts
  • 2.
  • 3. 2 144677 3 028 4 1 1. Organizing Numerical Data Numerical Data Ordered Array Stem and Leaf Display Frequency Distributions Cumulative Distributions Histograms Polygons Ogive Tables 41, 24, 32, 26, 27, 27, 30, 24, 38, 21 21, 24, 24, 26, 27, 27, 30, 32, 38, 41
  • 4.
  • 5. 2 144677 3 028 4 1 Organizing Numerical Data Numerical Data Ordered Array Stem and Leaf Display Histograms Ogive Tables 41, 24, 32, 26, 27, 27, 30, 24, 38, 21 21, 24, 24, 26, 27, 27, 30, 32, 38, 41 Frequency Distributions Cumulative Distributions Polygons
  • 6.
  • 7. Tabulating Numerical Data: Frequency Distributions Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Frequency 10 but under 20 3 .15 15 20 but under 30 6 .30 30 30 but under 40 5 .25 25 40 but under 50 4 .20 20 50 but under 60 2 .10 10 Total 20 1 100 Relative Frequency Percentage
  • 8. Graphing Numerical Data: The Histogram Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Midpoints No Gaps Between Bars
  • 9. Graphing Numerical Data: The Frequency Polygon Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Midpoints
  • 10. Cumulative Cumulative Class Frequency % Frequency 10 but under 20 3 15 20 but under 30 9 45 30 but under 40 14 70 40 but under 50 18 90 50 but under 60 20 100 Tabulating Numerical Data: Cumulative Frequency Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58
  • 11. Graphing Numerical Data: The Ogive (Cumulative % Polygon) Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Class Boundaries
  • 12. 3.Organizing Categorical Data Univariate Data: Categorical Data Tabulating Data The Summary Table Graphing Data Pie Charts Pareto Diagram Bar Charts
  • 13. Summary Table (for an investor’s portfolio) Investment Category Amount Percentage (in thousands $) Stocks 46.5 42.27 Bonds 32 29.09 CD 15.5 14.09 Savings 16 14.55 Total 110 100 Variables are Categorical.
  • 14. 4.Organizing Categorical Data Univariate Data: Categorical Data Tabulating Data The Summary Table Graphing Data Pie Charts Pareto Diagram Bar Charts
  • 15. Bar Chart (for an investor’s portfolio)
  • 16. Pie Chart (for an investor’s portfolio) Percentages are rounded to the nearest percent. Amount Invested in K$ Savings 15% CD 14% Bonds 29% Stocks 42%
  • 17. Pareto Diagram Axis for bar chart shows % invested in each category. Axis for line graph shows cumulative % invested .
  • 18.
  • 19. Organizing Categorical Data Bivariate Data: Contingency Table: Investment in Thousands of Dollars Investment Investor A Investor B Investor C Total Category Stocks 46.5 55 27.5 129 Bonds 32 44 19 95 CD 15.5 20 13.5 49 Savings 16 28 7 51 Total 110 147 67 324
  • 20. Organizing Categorical Data Bivariate Data: Side by Side Chart
  • 21.
  • 22.
  • 23. ‘ Chart Junk’ Good Presentation 1960: $1.00 1970: $1.60 1980: $3.10 1990: $3.80 Minimum Wage Minimum Wage 0 2 4 1960 1970 1980 1990 $ Bad Presentation 
  • 24. No Relative Basis Good Presentation A’s received by students. A’s received by students. Bad Presentation 0  200 300 FR SO JR SR Freq.  10%  30% FR SO JR SR % FR = Freshmen, SO = Sophomore, JR = Junior, SR = Senior 
  • 25. Compressing Vertical Axis Good Presentation Quarterly Sales Quarterly Sales Bad Presentation 0 25 50 Q1 Q2 Q3 Q4 $ 0 100 200 Q1 Q2 Q3 Q4 $ 
  • 26. No Zero Point on Vertical Axis Good Presentation Monthly Sales Monthly Sales Bad Presentation 0 39 42 45 J F M A M J $ 36 39 42 45 J F M A M J $ Graphing the first six months of sales. 36 
  • 27. No Zero Point on Vertical Axis Good Presentation Monthly Sales Monthly Sales Bad Presentation 0 20 40 60 J F M A M J $ 36 39 42 45 J F M A M J $ Graphing the first six months of sales. 
  • 28.
  翻译：