SlideShare a Scribd company logo
1 of 28
© 2002 Prentice-Hall, Inc. Chap 1-1
Basic Business Statistics
(8th Edition)
Chapter 1
Introduction and Data Collection
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-2
Chapter Topics
 Why a manager needs to know about
statistics
 The growth and development of modern
statistics
 Key definitions
 Descriptive versus inferential statistics
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-3
Chapter Topics
 Why data are needed
 Types of data and their sources
 Design of survey research
 Types of sampling methods
 Types of survey errors
(continued)
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-4
Why a Manager Needs to
Know about Statistics
 To know how to properly present
information
 To know how to draw conclusions
about populations based on sample
information
 To know how to improve processes
 To know how to obtain reliable
forecasts
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-5
The Growth and Development
of Modern Statistics
Needs of government to
collect data on its citizens
The development of the
mathematics of probability
theory
The advent of the computer
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-6
Key Definitions
 A population (universe) is the collection of
things under consideration
 A sample is a portion of the population
selected for analysis
 A parameter is a summary measure
computed to describe a characteristic of the
population
 A statistic is a summary measure computed
to describe a characteristic of the sample
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-7
Population and Sample
Population Sample
Use parameters to
summarize features
Use statistics to
summarize features
Inference on the population from the sample
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-8
Statistical Methods
 Descriptive statistics
 Collecting and describing data
 Inferential statistics
 Drawing conclusions and/or making
decisions concerning a population based
only on sample data
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-9
Descriptive Statistics
 Collect data
 e.g. Survey
 Present data
 e.g. Tables and graphs
 Characterize data
 e.g. Sample mean =
i
X
n

Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-10
Inferential Statistics
 Estimation
 e.g.: Estimate the population
mean weight using the
sample mean weight
 Hypothesis testing
 e.g.: Test the claim that the
population mean weight is
120 pounds
Drawing conclusions and/or making decisions
concerning a population based on sample results.
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-11
Why We Need Data
 To provide input to survey
 To provide input to study
 To measure performance of service or
production process
 To evaluate conformance to standards
 To assist in formulating alternative courses
of action
 To satisfy curiosity
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-12
Data Sources
Primary
Data Collection
Secondary
Data Compilation
Observation
Experimentation
Survey
Print or Electronic
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-13
Types of Data
Categorical
(Qualitative)
Discrete Continuous
Numerical
(Quantitative)
Data
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-14
Design of Survey Research
 Choose an appropriate mode of response
 Reliable primary modes
 Personal interview
 Telephone interview
 Mail survey
 Less reliable self-selection modes (not appropriate
for making inferences about the population)
 Television survey
 Internet survey
 Printed survey on newspapers and magazines
 Product or service questionnaires
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-15
Design of Survey Research
 Identify broad categories
 List complete and non-overlapping categories
that reflect the theme
 Formulate accurate questions
 Make questions clear and unambiguous. Use
universally-accepted definitions
 Test the survey
 Pilot test the survey on a small group of
participants to assess clarity and length
(continued)
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-16
Design of Survey Research
 Write a cover letter
 State the goal and purpose of the survey
 Explain the importance of a response
 Provide assurance of respondent’s anonymity
 Offer incentive gift for respondent participation
(continued)
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-17
Reasons for Drawing a Sample
 Less time consuming than a census
 Less costly to administer than a census
 Less cumbersome and more practical to
administer than a census of the targeted
population
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-18
Types of Sampling Methods
Quota
Samples
Non-Probability
Samples
Judgement Chunk
Probability Samples
Simple
Random
Systematic
Stratified
Cluster
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-19
Probability Sampling
 Subjects of the sample are chosen based on
known probabilities
Probability Samples
Simple
Random
Systematic Stratified Cluster
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-20
Simple Random Samples
 Every individual or item from the frame has an
equal chance of being selected
 Selection may be with replacement or without
replacement
 Samples obtained from table of random
numbers or computer random number
generators
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-21
 Decide on sample size: n
 Divide frame of N individuals into groups of k
individuals: k=n/n
 Randomly select one individual from the 1st
group
 Select every k-th individual thereafter
Systematic Samples
N = 64
n = 8
k = 8
First Group
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-22
Stratified Samples
 Population divided into two or more groups
according to some common characteristic
 Simple random sample selected from each
group
 The two or more samples are combined into
one
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-23
Cluster Samples
 Population divided into several “clusters,” each
representative of the population
 Simple random sample selected from each
 The samples are combined into one
Population
divided
into 4
clusters.
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-24
Advantages and Disadvantages
 Simple random sample and systematic sample
 Simple to use
 May not be a good representation of the
population’s underlying characteristics
 Stratified sample
 Ensures representation of individuals across the
entire population
 Cluster sample
 More cost effective
 Less efficient (need larger sample to acquire the
same level of precision)
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-25
Evaluating Survey Worthiness
 What is the purpose of the survey?
 Is the survey based on a probability sample?
 Coverage error – appropriate frame
 Nonresponse error – follow up
 Measurement error – good questions elicit
good responses
 Sampling error – always exists
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-26
Types of Survey Errors
 Coverage error
 Non response error
 Sampling error
 Measurement error
Excluded from
frame.
Follow up on
non responses.
Chance
differences from
sample to sample.
Bad Question!
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-27
Chapter Summary
 Addressed why a manager needs to know
about statistics
 Discussed the growth and development of
modern statistics
 Addressed the notion of descriptive versus
inferential statistics
 Discussed the importance of data
Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-28
Chapter Summary
 Defined and described the different types of
data and sources
 Discussed the design of survey
 Discussed types of sampling methods
 Described different types of survey errors
(continued)

More Related Content

Similar to chap01.ppt

data collection for elementary statistics by Taban Rashid
data collection for elementary statistics  by Taban Rashiddata collection for elementary statistics  by Taban Rashid
data collection for elementary statistics by Taban RashidRashidTaban
 
Chap01 intro & data collection
Chap01 intro & data collectionChap01 intro & data collection
Chap01 intro & data collectionUni Azza Aunillah
 
2012 data analysis
2012 data analysis2012 data analysis
2012 data analysischerylyap61
 
Business Statistics Chapter 1
Business Statistics Chapter 1Business Statistics Chapter 1
Business Statistics Chapter 1Lux PP
 
Bbs11 ppt ch07
Bbs11 ppt ch07Bbs11 ppt ch07
Bbs11 ppt ch07Tuul Tuul
 
Comment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docx
Comment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docxComment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docx
Comment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docxmccormicknadine86
 
Marketing Research (Marketing, 8th Edition)
Marketing Research (Marketing, 8th Edition)Marketing Research (Marketing, 8th Edition)
Marketing Research (Marketing, 8th Edition)Matthew A. Gilbert, MBA
 
User Group Kickoff and New Product Roadmap - HAS Session 12
User Group Kickoff and New Product Roadmap - HAS Session 12User Group Kickoff and New Product Roadmap - HAS Session 12
User Group Kickoff and New Product Roadmap - HAS Session 12Health Catalyst
 
Paper 9: Innovation Assessment and Improvement (D. Xu)
Paper 9: Innovation Assessment and Improvement (D. Xu)Paper 9: Innovation Assessment and Improvement (D. Xu)
Paper 9: Innovation Assessment and Improvement (D. Xu)Kent Business School
 
Basics (Reports Writing 2)
Basics (Reports Writing 2)Basics (Reports Writing 2)
Basics (Reports Writing 2)julianmillar
 
information retrival evaluation.ppt
information retrival evaluation.pptinformation retrival evaluation.ppt
information retrival evaluation.pptBonnieKabiru
 
Industrial Marketing Research, Marketing Intelligence & Decision Support System
Industrial Marketing Research, Marketing Intelligence & Decision Support SystemIndustrial Marketing Research, Marketing Intelligence & Decision Support System
Industrial Marketing Research, Marketing Intelligence & Decision Support Systemmsrim
 
Forecasting-Exponential Smoothing
Forecasting-Exponential SmoothingForecasting-Exponential Smoothing
Forecasting-Exponential Smoothingiceu novida adinata
 
Introduction to data science
Introduction to data scienceIntroduction to data science
Introduction to data scienceKoo Ping Shung
 

Similar to chap01.ppt (20)

data collection for elementary statistics by Taban Rashid
data collection for elementary statistics  by Taban Rashiddata collection for elementary statistics  by Taban Rashid
data collection for elementary statistics by Taban Rashid
 
Chap01 intro & data collection
Chap01 intro & data collectionChap01 intro & data collection
Chap01 intro & data collection
 
2012 data analysis
2012 data analysis2012 data analysis
2012 data analysis
 
Business Statistics Chapter 1
Business Statistics Chapter 1Business Statistics Chapter 1
Business Statistics Chapter 1
 
Chap09
Chap09Chap09
Chap09
 
Chap04
Chap04Chap04
Chap04
 
Lecture-1 Introduction to statistics.ppt
Lecture-1 Introduction to statistics.pptLecture-1 Introduction to statistics.ppt
Lecture-1 Introduction to statistics.ppt
 
Bbs11 ppt ch07
Bbs11 ppt ch07Bbs11 ppt ch07
Bbs11 ppt ch07
 
Comment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docx
Comment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docxComment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docx
Comment this post (DL) W3-T1Pricewaterhouse Coopers is one of th.docx
 
Marketing Research (Marketing, 8th Edition)
Marketing Research (Marketing, 8th Edition)Marketing Research (Marketing, 8th Edition)
Marketing Research (Marketing, 8th Edition)
 
User Group Kickoff and New Product Roadmap - HAS Session 12
User Group Kickoff and New Product Roadmap - HAS Session 12User Group Kickoff and New Product Roadmap - HAS Session 12
User Group Kickoff and New Product Roadmap - HAS Session 12
 
Paper 9: Innovation Assessment and Improvement (D. Xu)
Paper 9: Innovation Assessment and Improvement (D. Xu)Paper 9: Innovation Assessment and Improvement (D. Xu)
Paper 9: Innovation Assessment and Improvement (D. Xu)
 
Basics (Reports Writing 2)
Basics (Reports Writing 2)Basics (Reports Writing 2)
Basics (Reports Writing 2)
 
information retrival evaluation.ppt
information retrival evaluation.pptinformation retrival evaluation.ppt
information retrival evaluation.ppt
 
Industrial Marketing Research, Marketing Intelligence & Decision Support System
Industrial Marketing Research, Marketing Intelligence & Decision Support SystemIndustrial Marketing Research, Marketing Intelligence & Decision Support System
Industrial Marketing Research, Marketing Intelligence & Decision Support System
 
Forecasting-Exponential Smoothing
Forecasting-Exponential SmoothingForecasting-Exponential Smoothing
Forecasting-Exponential Smoothing
 
Research process
Research processResearch process
Research process
 
Introduction to data science
Introduction to data scienceIntroduction to data science
Introduction to data science
 
Research CHap 4
Research CHap 4Research CHap 4
Research CHap 4
 
Making sense of numbers - a half-day workshop
Making sense of numbers - a half-day workshopMaking sense of numbers - a half-day workshop
Making sense of numbers - a half-day workshop
 

Recently uploaded

Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxmanuelaromero2013
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
mini mental status format.docx
mini    mental       status     format.docxmini    mental       status     format.docx
mini mental status format.docxPoojaSen20
 
Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...
Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...
Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...RKavithamani
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfchloefrazer622
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application ) Sakshi Ghasle
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 

Recently uploaded (20)

Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptx
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
mini mental status format.docx
mini    mental       status     format.docxmini    mental       status     format.docx
mini mental status format.docx
 
Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...
Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...
Privatization and Disinvestment - Meaning, Objectives, Advantages and Disadva...
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdf
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application )
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 

chap01.ppt

  • 1. © 2002 Prentice-Hall, Inc. Chap 1-1 Basic Business Statistics (8th Edition) Chapter 1 Introduction and Data Collection
  • 2. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-2 Chapter Topics  Why a manager needs to know about statistics  The growth and development of modern statistics  Key definitions  Descriptive versus inferential statistics
  • 3. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-3 Chapter Topics  Why data are needed  Types of data and their sources  Design of survey research  Types of sampling methods  Types of survey errors (continued)
  • 4. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-4 Why a Manager Needs to Know about Statistics  To know how to properly present information  To know how to draw conclusions about populations based on sample information  To know how to improve processes  To know how to obtain reliable forecasts
  • 5. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-5 The Growth and Development of Modern Statistics Needs of government to collect data on its citizens The development of the mathematics of probability theory The advent of the computer
  • 6. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-6 Key Definitions  A population (universe) is the collection of things under consideration  A sample is a portion of the population selected for analysis  A parameter is a summary measure computed to describe a characteristic of the population  A statistic is a summary measure computed to describe a characteristic of the sample
  • 7. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-7 Population and Sample Population Sample Use parameters to summarize features Use statistics to summarize features Inference on the population from the sample
  • 8. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-8 Statistical Methods  Descriptive statistics  Collecting and describing data  Inferential statistics  Drawing conclusions and/or making decisions concerning a population based only on sample data
  • 9. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-9 Descriptive Statistics  Collect data  e.g. Survey  Present data  e.g. Tables and graphs  Characterize data  e.g. Sample mean = i X n 
  • 10. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-10 Inferential Statistics  Estimation  e.g.: Estimate the population mean weight using the sample mean weight  Hypothesis testing  e.g.: Test the claim that the population mean weight is 120 pounds Drawing conclusions and/or making decisions concerning a population based on sample results.
  • 11. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-11 Why We Need Data  To provide input to survey  To provide input to study  To measure performance of service or production process  To evaluate conformance to standards  To assist in formulating alternative courses of action  To satisfy curiosity
  • 12. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-12 Data Sources Primary Data Collection Secondary Data Compilation Observation Experimentation Survey Print or Electronic
  • 13. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-13 Types of Data Categorical (Qualitative) Discrete Continuous Numerical (Quantitative) Data
  • 14. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-14 Design of Survey Research  Choose an appropriate mode of response  Reliable primary modes  Personal interview  Telephone interview  Mail survey  Less reliable self-selection modes (not appropriate for making inferences about the population)  Television survey  Internet survey  Printed survey on newspapers and magazines  Product or service questionnaires
  • 15. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-15 Design of Survey Research  Identify broad categories  List complete and non-overlapping categories that reflect the theme  Formulate accurate questions  Make questions clear and unambiguous. Use universally-accepted definitions  Test the survey  Pilot test the survey on a small group of participants to assess clarity and length (continued)
  • 16. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-16 Design of Survey Research  Write a cover letter  State the goal and purpose of the survey  Explain the importance of a response  Provide assurance of respondent’s anonymity  Offer incentive gift for respondent participation (continued)
  • 17. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-17 Reasons for Drawing a Sample  Less time consuming than a census  Less costly to administer than a census  Less cumbersome and more practical to administer than a census of the targeted population
  • 18. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-18 Types of Sampling Methods Quota Samples Non-Probability Samples Judgement Chunk Probability Samples Simple Random Systematic Stratified Cluster
  • 19. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-19 Probability Sampling  Subjects of the sample are chosen based on known probabilities Probability Samples Simple Random Systematic Stratified Cluster
  • 20. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-20 Simple Random Samples  Every individual or item from the frame has an equal chance of being selected  Selection may be with replacement or without replacement  Samples obtained from table of random numbers or computer random number generators
  • 21. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-21  Decide on sample size: n  Divide frame of N individuals into groups of k individuals: k=n/n  Randomly select one individual from the 1st group  Select every k-th individual thereafter Systematic Samples N = 64 n = 8 k = 8 First Group
  • 22. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-22 Stratified Samples  Population divided into two or more groups according to some common characteristic  Simple random sample selected from each group  The two or more samples are combined into one
  • 23. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-23 Cluster Samples  Population divided into several “clusters,” each representative of the population  Simple random sample selected from each  The samples are combined into one Population divided into 4 clusters.
  • 24. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-24 Advantages and Disadvantages  Simple random sample and systematic sample  Simple to use  May not be a good representation of the population’s underlying characteristics  Stratified sample  Ensures representation of individuals across the entire population  Cluster sample  More cost effective  Less efficient (need larger sample to acquire the same level of precision)
  • 25. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-25 Evaluating Survey Worthiness  What is the purpose of the survey?  Is the survey based on a probability sample?  Coverage error – appropriate frame  Nonresponse error – follow up  Measurement error – good questions elicit good responses  Sampling error – always exists
  • 26. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-26 Types of Survey Errors  Coverage error  Non response error  Sampling error  Measurement error Excluded from frame. Follow up on non responses. Chance differences from sample to sample. Bad Question!
  • 27. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-27 Chapter Summary  Addressed why a manager needs to know about statistics  Discussed the growth and development of modern statistics  Addressed the notion of descriptive versus inferential statistics  Discussed the importance of data
  • 28. Basic Business Statistics, 8e © 2002 Prentice-Hall, Inc. Chap 1-28 Chapter Summary  Defined and described the different types of data and sources  Discussed the design of survey  Discussed types of sampling methods  Described different types of survey errors (continued)