## Essentials of Statistics for Business & Economics 9th Edition

### Essentials of Statistics for Business & Economics Ninth Edition:

**Additional ISBNs:**

**âˆ— eText ISBN: **0357118197, 978-0357118191, 9780357118191

- See additional information on the Amazon.

##### More Details

**Essentials of Statistics for Business & Economics 9th Edition:**

Brief Contents

Contents

About the Authors

Preface

Chapter 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 Analytics

1.7 Big Data and Data Mining

1.8 Computers and Statistical Analysis

1.9 Ethical Guidelines for Statistical Practice

Summary

Glossary

Supplementary Exercises

Chapter 1 Appendix

Chapter 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: Movie Theater Releases

Case Problem 3: Queen City

Case Problem 4: Cut-Rate Machining, Inc.

Chapter 2 Appendix

Chapter 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 Boxplots

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: Movie Theater Releases

Case Problem 3: Business Schools of Asia-Pacific

Case Problem 4: Heavenly Chocolates Website Transactions

Case Problem 5: African Elephant Populations

Chapter 3 Appendix

Chapter 4: Introduction to Probability

4.1 Random 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 1: Hamilton County Judges

Case Problem 2: Rob’s Market

Chapter 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

5.6 Poisson Probability Distribution

5.7 Hypergeometric Probability Distribution

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Go Bananas! Breakfast Cereal

Case Problem 2: McNeil’s Auto Mall

Case Problem 3: Grievance Committee at Tuglar Corporation

Chapter 5 Appendix

Chapter 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 1: Specialty Toys

Case Problem 2: Gebhardt Electronics

Chapter 6 Appendix

Chapter 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

7.9 Big Data and Standard Errors of Sampling Distributions

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem: Marion Dairies

Chapter 7 Appendix

Chapter 8: Interval Estimation

8.1 Population Mean: o Known

8.2 Population Mean: o Unknown

8.3 Determining the Sample Size

8.5 Big Data and Confidence Intervals

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.

Chapter 8 Appendix

Chapter 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

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

9.9 Big Data and Hypothesis Testing

Summary

Glossary

Key Formulas

Supplementary Exercises

Case Problem 1: Quality Associates, Inc.

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

Chapter 9 Appendix

Chapter 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.

Chapter 10 Appendix

Chapter 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 1: Air Force Training Program

Case Problem 2: Meticulous Drill & Reamer

Chapter 11 Appendix

Chapter 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 1: A Bipartisan Agenda for Change

Case Problem 2: Fuentes Salty Snacks, Inc.

Case Problem 3: Fresno Board Games

Chapter 12 Appendix

Chapter 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

Case Problem 3: TourisTopia Travel

Chapter 13 Appendix

Chapter 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

14.10 Practical Advice: Big Data and Hypothesis Testing in Simple Linear Regression

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

Case Problem 5: Buckeye Creek Amusement Park

Chapter 14 Appendix

Chapter 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

15.10 Practical Advice: Big Data and Hypothesis Testing in Multiple 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

Chapter 15 Appendix

Appendix A – References and Bibliography

Appendix B – Tables

Appendix C – Summation Notation

Appendix E – Microsoft Excel 2016 and Tools for Statistical Analysis

Appendix F – Computing p-Values with JMP and Excel

Index

## Reviews

There are no reviews yet.