### Solution Manual For Statistics for Business and Economics 12th Edition David Anderson

#### Solution Manual For Statistics for Business and Economics 12th Edition David Anderson

The authors bring more than twenty-five years of unmatched experience to this text, along with sound statistical methodology, a proven problem-scenario approach, and meaningful applications that clearly demonstrate how statistical information informs decisions in the business world. Thoroughly updated, the text’s more than 350 real business examples, cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. And, to give you the most relevant text you can get for your course, you select the topics you want, including coverage of popular commercial statistical software programs like Minitab 16 and Excel 2013, along with StatTools and other leading Excel 2013 statistical add-ins

### Additional ISBNs

1305264339, 128584632X, 1305458567, 9781305264335, 9781305458567, 1337028126, 9781305457324, 9781337028127

## Table of Content

Brief Contents

Contents

Preface

About the Authors

Ch 1: Data and Statistics

1.1 Applications in Business and Economics

1.2 Data

1.3 Data Sources

1.4 Descriptive Statistics

1.5 Statistical Inference

1.6 Computers and Statistical Analysis

1.7 Data Mining

1.8 Ethical Guidelines for Statistical Practice

Summary

Glossary

Supplementary Exercises

Appendix: An Introduction to StatTools

Ch 2: Descriptive Statistics: Tabular and Graphical Displays

2.1 Summarizing Data for a Categorical Variable

2.2 Summarizing Data for a Quantitative Variable

2.3 Summarizing Data for Two Variables Using Tables

2.4 Summarizing Data for Two Variables Using Graphical Displays

2.5 Data Visualization: Best Practices in Creating Effective Graphical Displays

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Pelican Stores

Case Problem 2: Motion Picture Industry

Appendix 2.1 Using Minitab for Tabular and Graphical Presentations

Appendix 2.2 Using Excel for Tabular and Graphical Presentations

Appendix 2.3 Using StatTools for Tabular and Graphical Presentations

Ch 3: Descriptive Statistics: Numerical Measures

3.1 Measures of Location

3.2 Measures of Variability

3.3 Measures of Distribution Shape, Relative Location, and Detecting Outliers

3.4 Five-Number Summaries and Box Plots

3.5 Measures of Association between Two Variables

3.6 Data Dashboards: Adding Numerical Measures to Improve Effectiveness

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Pelican Stores

Case Problem 2: Motion Picture Industry

Case Problem 3: Business Schools of Asia-Pacific

Case Problem 4: Heavenly Chocolates Website Transactions

Case Problem 5: African Elephant Populations

Appendix 3.1 Descriptive Statistics Using Minitab

Appendix 3.2 Descriptive Statistics Using Excel

Appendix 3.3 Descriptive Statistics Using StatTools

Ch 4: Introduction to Probability

4.1 Experiments, Counting Rules, and Assigning Probabilities

4.2 Events and Their Probabilities

4.3 Some Basic Relationships of Probability

4.4 Conditional Probability

4.5 Bayes’ Theorem

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem: Hamilton County Judges

Ch 5: Discrete Probability Distributions

5.1 Random Variables

5.2 Developing Discrete Probability Distributions

5.3 Expected Value and Variance

5.4 Bivariate Distributions, Covariance, and Financial Portfolios

5.5 Binomial Probability Distribution

5.6 Poisson Probability Distribution

5.7 Hypergeometric Probability Distribution

Summary

Glossary

Key Formulas

Supplementary Exercises

Appendix 5.1 Discrete Probability Distributions with Minitab

Appendix 5.2 Discrete Probability Distributions with Excel

Ch 6: Continuous Probability Distributions

6.1 Uniform Probability Distribution

6.2 Normal Probability Distribution

6.3 Normal Approximation of Binomial Probabilities

6.4 Exponential Probability Distribution

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem: Specialty Toys

Appendix 6.1 Continuous Probability Distributions with Minitab

Appendix 6.2 Continuous Probability Distributions with Excel

Ch 7: Sampling and Sampling Distributions

7.1 The Electronics Associates Sampling Problem

7.2 Selecting a Sample

7.3 Point Estimation

7.4 Introduction to Sampling Distributions

7.5 Sampling Distribution of x

7.6 Sampling Distribution of p

7.7 Properties of Point Estimators

7.8 Other Sampling Methods

Summary

Glossary

Key Formulas

Supplementary Exercises

Appendix 7.1 The Expected Value and Standard Deviation of x

Appendix 7.2 Random Sampling with Minitab

Appendix 7.3 Random Sampling with Excel

Appendix 7.4 Random Sampling with StatTools

Ch 8: Interval Estimation

8.1 Population Mean: o Known

8.2 Population Mean: o Unknown

8.3 Determining the Sample Size

8.4 Population Proportion

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Young Professional Magazine

Case Problem 2: Gulf Real Estate Properties

Case Problem 3: Metropolitan Research, Inc.

Appendix 8.1 Interval Estimation with Minitab

Appendix 8.2 Interval Estimation Using Excel

Appendix 8.3 Interval Estimation with StatTools

Ch 9: Hypothesis Tests

9.1 Developing Null and Alternative Hypotheses

9.2 Type I and Type II Errors

9.3 Population Mean: o Known

9.4 Population Mean: o Unknown

9.5 Population Proportion

9.6 Hypothesis Testing and Decision Making

9.7 Calculating the Probability of Type II Errors

9.8 Determining the Sample Size for a Hypothesis Test about a Population Mean

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Quality Associates, Inc.

Case Problem 2: Ethical Behavior of Business Students at Bayview University

Appendix 9.1 Hypothesis Testing with Minitab

Appendix 9.2 Hypothesis Testing with Excel

Appendix 9.3 Hypothesis Testing with StatTools

Ch 10: Inference about Means and Proportions with Two Populations

10.1 Inferences about the Difference between Two Population Means: o1 and o2 Known

10.2 Inferences about the Difference between Two Population Means: o1 and o2 Unknown

10.3 Inferences about the Difference between Two Population Means: Matched Samples

10.4 Inferences about the Difference between Two Population Proportions

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem: Par, Inc.

Appendix 10.1 Inferences about Two Populations Using Minitab

Appendix 10.2 Inferences about Two Populations Using Excel

Appendix 10.3 Inferences about Two Populations Using StatTools

Ch 11: Inferences about Population Variances

11.1 Inferences about a Population Variance

11.2 Inferences about Two Population Variances

Summary

Key Formulas

Supplementary Exercises

Case Problem: Air Force Training Program

Appendix 11.1 Population Variances with Minitab

Appendix 11.2 Population Variances with Excel

Appendix 11.3 Single Population Standard Deviation with StatTools

Ch 12: Comparing Multiple Proportions, Test of Independence and Goodness of Fit

12.1 Testing the Equality of Population Proportions for Three or More Populations

12.2 Test of Independence

12.3 Goodness of Fit Test

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem: A Bipartisan Agenda for Change

Appendix 12.1 Chi-Square Tests Using Minitab

Appendix 12.2 Chi-Square Tests Using Excel

Appendix 12.3 Chi-Square Tests Using StatTools

Ch 13: Experimental Design and Analysis of Variance

13.1 An Introduction to Experimental Design and Analysis of Variance

13.2 Analysis of Variance and the Completely Randomized Design

13.3 Multiple Comparison Procedures

13.4 Randomized Block Design

13.5 Factorial Experiment

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Wentworth Medical Center

Case Problem 2: Compensation for Sales Professionals

Appendix 13.1 Analysis of Variance with Minitab

Appendix 13.2 Analysis of Variance with Excel

Appendix 13.3 Analysis of a Completely Randomized Design Using StatTools

Ch 14: Simple Linear Regression

14.1 Simple Linear Regression Model

14.2 Least Squares Method

14.3 Coefficient of Determination

14.4 Model Assumptions

14.5 Testing for Significance

14.6 Using the Estimated Regression Equation for Estimation and Prediction

14.7 Computer Solution

14.8 Residual Analysis: Validating Model Assumptions

14.9 Residual Analysis: Outliers and Influential Observations

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Measuring Stock Market Risk

Case Problem 2: U.S. Department of Transportation

Case Problem 3: Selecting a Point-and-Shoot Digital Camera

Case Problem 4: Finding the Best Car Value

Appendix 14.1 Calculus-Based Derivation of Least Squares Formulas

Appendix 14.2 A Test for Significance Using Correlation

Appendix 14.3 Regression Analysis with Minitab

Appendix 14.4 Regression Analysis with Excel

Appendix 14.5 Regression Analysis Using StatTools

Ch 15: Multiple Regression

15.1 Multiple Regression Model

15.2 Least Squares Method

15.3 Multiple Coefficient of Determination

15.4 Model Assumptions

15.5 Testing for Significance

15.6 Using the Estimated Regression Equation for Estimation and Prediction

15.7 Categorical Independent Variables

15.8 Residual Analysis

15.9 Logistic Regression

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Consumer Research, Inc.

Case Problem 2: Predicting Winnings for NASCAR Drivers

Case Problem 3: Finding the Best Car Value

Appendix 15.1 Multiple Regression with Minitab

Appendix 15.2 Multiple Regression with Excel

Appendix 15.3 Logistic Regression with Minitab

Appendix 15.4 Multiple Regression Analysis Using StatTools

Ch 16: Regression Analysis: Model Building

16.1 General Linear Model

16.2 Determining When to Add or Delete Variables

16.3 Analysis of a Larger Problem

16.4 Variable Selection Procedures

16.5 Multiple Regression Approach to Experimental Design

16.6 Autocorrelation and the Durbin-Watson Test

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Analysis of PGA Tour Statistics

Case Problem 2: Rating Wines from the Piedmont Region of Italy

Appendix 16.1 Variable Selection Procedures with Minitab

Appendix 16.2 Variable Selection Procedures Using StatTools

Ch 17: Time Series Analysis and Forecasting

17.1 Time Series Patterns

17.2 Forecast Accuracy

17.3 Moving Averages and Exponential Smoothing

17.4 Trend Projection

17.5 Seasonality and Trend

17.6 Time Series Decomposition

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Forecasting Food and Beverage Sales

Case Problem 2: Forecasting Lost Sales

Appendix 17.1 Forecasting with Minitab

Appendix 17.2 Forecasting with Excel

Appendix 17.3 Forecasting Using StatTools

Ch 18: Nonparametric Methods

18.1 Sign Test

18.2 Wilcoxon Signed-Rank Test

18.3 Mann-Whitney-Wilcoxon Test

18.4 Kruskal-Wallis Test

18.5 Rank Correlation

Summary

Glossary

Key Formulas

Supplementary Exercises

Appendix 18.1 Nonparametric Methods with Minitab

Appendix 18.2 Nonparametric Methods with Excel

Appendix 18.3 Nonparametric Methods with StatTools

Ch 19: Statistical Methods for Quality Control

19.1 Philosophies and Frameworks

19.2 Statistical Process Control

19.3 Acceptance Sampling

Summary

Glossary

Key Formulas

Supplementary Exercises

Appendix 19.1 Control Charts with Minitab

Appendix 19.2 Control Charts Using StatTools

Ch 20: Index Numbers

20.1 Price Relatives

20.2 Aggregate Price Indexes

20.3 Computing an Aggregate Price Index from Price Relatives

20.4 Some Important Price Indexes

20.5 Deflating a Series by Price Indexes

20.6 Price Indexes: Other Considerations

20.7 Quantity Indexes

Summary

Glossary

Key Formulas

Supplementary Exercises

Appendix A: References and Bibliography

Appendix B: Tables

Appendix C: Summation Notation

Appendix D: Self-Test Solutions and Answers to Even-Numbered Exercises

Appendix E: Microsoft Excel 2013 and Tools for Statistical Analysis

Appendix F: Computing p-Values Using Minitab and Excel

Index

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