Chapter 1 Student Lecture Notes 1-1 Basic Business Statistics (9th Edition) Chapter 1 Introduction and Data Collection © 2004 Prentice-Hall, Inc. Chap 1-1 Chapter Topics Why a Manager Needs to Know About Statistics The Growth and Development of Modern Statistics Some Important Definitions Descriptive Versus Inferential Statistics Chap 1-2 © 2004 Prentice-Hall, Inc. Chapter Topics Why Data Are Needed Types of Data and Their Sources Design of Survey Research Types of Survey Sampling Methods Evaluating Survey Worthiness Types of Survey Errors © 2004 Prentice-Hall, Inc. (continued) Chap 1-3 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-2 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 Chap 1-4 © 2004 Prentice-Hall, Inc. The Growth and Development of Modern Statistics Needs of government to collect data on its citizenry The development of the mathematics of probability theory The advent of the computer Chap 1-5 © 2004 Prentice-Hall, Inc. Some Important Definitions A Population (Universe) is the Whole 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 © 2004 Prentice-Hall, Inc. Chap 1-6 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-3 Population and Sample Population Sample Use statistics to summarize features Use parameters to summarize features Inference on the population from the sample Chap 1-7 © 2004 Prentice-Hall, Inc. Statistical Methods Descriptive Statistics Inferential Statistics Collecting, presenting, and characterizing data Drawing conclusions and/or making decisions concerning a population based only on sample data Chap 1-8 © 2004 Prentice-Hall, Inc. Descriptive Statistics Collect Data Present Data E.g., Survey E.g., Tables and graphs Characterize Data E.g., Sample Mean = © 2004 Prentice-Hall, Inc. ∑X i n Chap 1-9 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-4 Inferential Statistics Drawing conclusions and/or making decisions concerning a population based on sample results. 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 value is 120 pounds Chap 1-10 © 2004 Prentice-Hall, Inc. Why We Need Data To Provide Input to a Survey To Provide Input to a Study To Measure Performance of Ongoing Service or Production Process To Evaluate Conformance to Standards To Assist in Formulating Alternative Courses of Action To Satisfy Curiosity Chap 1-11 © 2004 Prentice-Hall, Inc. Data Sources Data Sources Print or Electronic Observation Survey Experimentation © 2004 Prentice-Hall, Inc. Chap 1-12 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-5 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 in newspapers and magazines Product or service questionnaires Chap 1-13 © 2004 Prentice-Hall, Inc. Design of Survey Research (continued) Identify Broad Categories Formulate Accurate Questions List complete and non-overlapping categories that reflect the theme Clear and unambiguous questions use clear operational definitions – universally accepted definitions Test the Survey Pilot test on a small group of participants to assess clarity and length Chap 1-14 © 2004 Prentice-Hall, Inc. Design of Survey Research (continued) Write a Cover Letter State the goal and purpose of the survey Explain the importance of a response Provide assurance of respondent anonymity Offer incentive gift for respondent participation © 2004 Prentice-Hall, Inc. Chap 1-15 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-6 Types of Data Data Categorical (Qualitative) Numerical (Quantitative) Discrete Continuous Chap 1-16 © 2004 Prentice-Hall, Inc. Type of Data (continued) Categorical random variables yield categorical responses E.g. Are you married? Yes or No Numerical random variables yield numerical responses Discrete random variables yield numerical response that arise from a counting process E.g. How many cars do you own? 3 cars Continuous random variables yield numerical responses that arise from a measuring process E.g. What is your weight? 130 pounds © 2004 Prentice-Hall, Inc. Chap 1-17 Levels of Measurement and Types of Measurement Scales Nominal Scale – distinct categories in which no ordering is implied E.g. Student grades: A, B, C, D or F Interval Scale – an ordered scale in which the difference between the measurements does not involve a true zero point E.g. Type of stocks invested: growth, income, other and none Ordinal Scale – distinct categories in which ordering is implied E.g. Temperature in degrees Celsius Ratio Scale – an ordered scale in which the difference between the measurements involves a true zero point E.g. Weight in pounds © 2004 Prentice-Hall, Inc. Chap 1-18 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-7 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 Population Chap 1-19 © 2004 Prentice-Hall, Inc. Types of Sampling Methods Samples Non-Probability Samples Judgement Chunk Probability Samples Simple Random Stratified Cluster Quota Convenience Systematic Chap 1-20 © 2004 Prentice-Hall, Inc. Probability Sampling Subjects of the Sample are Chosen Based on Known Probabilities Probability Samples Simple Random © 2004 Prentice-Hall, Inc. Systematic Stratified Cluster Chap 1-21 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-8 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 One May Use Table of Random Numbers or Computer Random Number Generators to Obtain Samples Chap 1-22 © 2004 Prentice-Hall, Inc. Systematic Samples 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 N = 64 n=8 © 2004 Prentice-Hall, Inc. First Group k=8 Chap 1-23 Stratified Samples Population Divided into 2 or More Groups According to Some Common Characteristic Simple Random Sample Selected from Each Group The Two or More Samples are Combined into One © 2004 Prentice-Hall, Inc. Chap 1-24 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-9 Cluster Samples Population Divided into Several “Clusters,” Each Representative of the Population A Random Sampling of Clusters is Taken All Items in the Selected Clusters are Studied Randomly selected 2 clusters Population divided into 4 clusters © 2004 Prentice-Hall, Inc. Chap 1-25 Advantages and Disadvantages Simple Random Sample & Systematic Sample Stratified Sample Simple to use May not be a good representation of the population’s underlying characteristics 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) © 2004 Prentice-Hall, Inc. Chap 1-26 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 © 2004 Prentice-Hall, Inc. Chap 1-27 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc. Chapter 1 Student Lecture Notes 1-10 Types of Survey Errors Coverage Error Excluded from frame Nonresponse Error Follow up on nonresponses Sampling Error Measurement Error Chance differences from sample to sample Bad Question! Chap 1-28 © 2004 Prentice-Hall, Inc. 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 Chap 1-29 © 2004 Prentice-Hall, Inc. Chapter Summary (continued) Defined and Described the Different Types of Data and Sources Discussed the Design of Surveys Discussed Types of Survey Sampling Methods Evaluated Survey Worthiness Described Different Types of Survey Errors © 2004 Prentice-Hall, Inc. Chap 1-30 Statistics for Managers Using Microsoft Excel, 2/e © 1999 Prentice-Hall, Inc.