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