## Description

### Test bank for Business Analytics Data Analysis and Decision Making 5th Edition by S. Christian Albright

#### Test bank for Business Analytics Data Analysis and Decision Making 5th Edition by S. Christian Albright

Become a master of data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 5E! This quantitative methods text provides users with the tools to succeed with a teach-by-example approach, student-friendly writing style, and complete Excel 2013 integration. It is also compatible with Excel 2010 and 2007. Problem sets and cases provide realistic examples to show the relevance of the material. The Companion Website includes: the Palisade DecisionTools Suite (@RISK, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver); SolverTable, which allows you to do sensitivity analysis; data and solutions files, PowerPoint slides, and tutorial videos.

About the Authors

Brief Contents

Contents

Preface

Ch 1: Introduction to Data Analysis and Decision Making

1-1: Introduction

1-2: Overview of the Book

1-3: Modeling and Models

1-4: Conclusion

Hottest New Jobs: Statistics and Mathematics

Part 1: Exploring Data

Ch 2: Describing the Distribution of a Single Variable

2-1: Introduction

2-2: Basic Concepts

2-3: Descriptive Measures for Categorical Variables

2-4: Descriptive Measures for Numerical Variables

2-5: Time Series Data

2-6: Outliers and Missing Values

2-7: Excel Tables for Filtering, Sorting, and Summarizing

2-8: Conclusion

Ch 3: Finding Relationships among Variables

3-1: Introduction

3-2: Relationships among Categorical Variables

3-3: Relationships among Categorical Variables and a Numerical Variable

3-4: Relationships among Numerical Variables

3-5: Pivot Tables

3-6: Conclusion

Part 2: Probability and Decision Making under Uncertainty

Ch 4: Probability and Probability Distributions

4-1: Introduction

4-2: Probability Essentials

4-3: Probability Distribution of a Single Random Variable

4-4: Introduction to Simulation

4-5: Conclusion

Ch 5: Normal, Binomial, Poisson, and Exponential Distributions

5-1: Introduction

5-2: The Normal Distribution

5-3: Applications of the Normal Distribution

5-4: The Binomial Distribution

5-5: Applications of the Binomial Distribution

5-6: The Poisson and Exponential Distributions

5-7: Conclusion

Ch 6: Decision Making under Uncertainty

6-1: Introduction

6-2: Elements of Decision Analysis

6-3: The Precisiontree Add-In

6-4: Bayes’ Rule

6-5: Multistage Decision Problems and the Value of Information

6-6: Risk Aversion and Expected Utility

6-7: Conclusion

Part 3: Statistical Inference

Ch 7: Sampling and Sampling Distributions

7-1: Introduction

7-2: Sampling Terminology

7-3: Methods for Selecting Random Samples

7-4: Introduction to Estimation

7-5: Conclusion

Ch 8: Confidence Interval Estimation

8-1: Introduction

8-2: Sampling Distributions

8-3: Confidence Interval for a Mean

8-4: Confidence Interval for a Total

8-5: Confidence Interval for a Proportion

8-6: Confidence Interval for a Standard Deviation

8-7: Confidence Interval for the Difference between Means

8-8: Confidence Interval for the Difference between Proportions

8-9: Sample Size Selection

8-10: Conclusion

Ch 9: Hypothesis Testing

9-1: Introduction

9-2: Concepts in Hypothesis Testing

9-3: Hypothesis Tests for a Population Mean

9-4: Hypothesis Tests for Other Parameters

9-5: Tests for Normality

9-6: Chi-Square Test for Independence

9-7: Conclusion

Part 4: Regression Analysis and Time Series Forecasting

Ch 10: Regression Analysis: Estimating Relationships

10-1: Introduction

10-2: Scatterplots: Graphing Relationships

10-3: Correlations: Indicators of Linear Relationships

10-4: Simple Linear Regression

10-5: Multiple Regression

10-6: Modeling Possibilities

10-7: Validation of the Fit

10-8: Conclusion

Ch 11: Regression Analysis: Statistical Inference

11-1: Introduction

11-2: The Statistical Model

11-3: Inferences about the Regression Coefficients

11-4: Multicollinearity

11-5: Include/Exclude Decisions

11-6: Stepwise Regression

11-7: Outliers

11-8: Violations of Regression Assumptions

11-9: Prediction

11-10: Conclusion

Ch 12: Time Series Analysis and Forecasting

12-1: Introduction

12-2: Forecasting Methods: An Overview

12-3: Testing for Randomness

12-4: Regression-Based Trend Models

12-5: The Random Walk Model

12-6: Moving Averages Forecasts

12-7: Exponential Smoothing Forecasts

12-8: Seasonal Models

12-9: Conclusion

Part 5: Optimization and Simulation Modeling

Ch 13: Introduction to Optimization Modeling

13-1: Introduction

13-2: Introduction to Optimization

13-3: A Two-Variable Product Mix Model

13-4: Sensitivity Analysis

13-5: Properties of Linear Models

13-6: Infeasibility and Unboundedness

13-7: A Larger Product Mix Model

13-8: A Multiperiod Production Model

13-9: A Comparison of Algebraic and Spreadsheet Models

13-10: A Decision Support System

13-11: Conclusion

Ch 14: Optimization Models

14-1: Introduction

14-2: Worker Scheduling Models

14-3: Blending Models

14-4: Logistics Models

14-5: Aggregate Planning Models

14-6: Financial Models

14-7: Integer Optimization Models

14-8: Nonlinear Optimization Models

14-9: Conclusion

Ch 15: Introduction to Simulation Modeling

15-1: Introduction

15-2: Probability Distributions for Input Variables

15-3: Simulation and the Flaw of Averages

15-4: Simulation with Built-In Excel Tools

15-5: Introduction to the @RISK

15-6: The Effects of Input Distributions on Results

15-7: Conclusion

Ch 16: Simulation Models

16-1: Introduction

16-2: Operations Models

16-3: Financial Models

16-4: Marketing Models

16-5: Simulating Games of Chance

16-6: An Automated Template for @RISK Models

16-7: Conclusion

Part 6: Advanced Data Analysis

Ch 17: Data Mining

17-1: Introduction

17-2: Data Exploration and Visualization

17-3: Microsoft Data Mining Add-Ins for Excel

17-4: Classification Methods

17-5: Clustering

17-6: Conclusion

Part 7: Bonus Online Material

Ch 18: Importing Data into Excel

18-1: Introduction

18-2: Rearranging Excel Data

18-3: Importing Text Data

18-4: Importing Relational Database Data

18-5: Web Queries

18-6: Cleansing Data

18-7: Conclusion

Ch 19: Analysis of Variance and Experimental Design

19-1: Introduction

19-2: One-Way ANOVA

19-3: Using Regression to Perform ANOVA

19-4: The Multiple Comparison Problem

19-5: Two-Way ANOVA

19-6: More about Experimental Design

19-7: Conclusion

Ch 20: Statistical Process Control

20-1: Introduction

20-2: Deming’s 14 Points

20-3: Introduction to Control Charts

20-4: Control Charts for Variables

20-5: Control Charts for Attributes

20-6: Process Capability

20-7: Conclusion

Appendix A: Statistical Reporting

A-1: Introduction

A-2: Suggestions for Good Statistical Reporting

A-3: Examples of Statistical Reports

A-4: Conclusion

References

Index

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#### Test bank for Business Analytics Data Analysis and Decision Making 5th Edition by S. Christian Albright