Data Analysis and Decision Making (with Online Content Printed Access Card)

by Albright, S. Christian; Winston, Wayne; Zappe, Christopher

• ISBN13: 9780538476126
• ISBN10: 0538476125
• Edition: 4th
• Format: Hardcover
• Copyright: 2010-10-12
• Publisher: South-Western College Pub

Summary

Data Analysis and Decision Making is a teach-by-example approach, learner-friendly writing style, and complete Excel integration focusing on data analysis, modeling, and spreadsheet use in statistics and management science.

The Premium Online Content Website (accessed by a unique code with every new book) includes links to the following add-ins: the Palisade Decision Tools Suite (@RISK, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver); and SolverTable, allowing users to do sensitivity analysis. All of the add-ins is revised for Excel 2007 and notes about Excel 2010 are added where applicable.

Review

"I want to commend you and your colleagues on Data Analysis and Decision Making. That textbook is one of the most well organized, well written and useful books I have used in either undergraduate or graduate studies. Any questionI had while going through the course was easy to find and well answered. The use of Excel and Palisades tools was excellent. Thank you for taking the time and effort to publish such a great reference. It will surely be on my bookshelf for many years."

Table of Contents

Preface

Introduction to Data Analysis and Decision Making

Introduction

An Overview of the Book

Modeling and Models

Conclusion

Exploring Data

Describing the Distribution of a Single Variable

Introduction

Basic Concepts

Descriptive Measures for Categorical Variables

Descriptive Measures for Numerical Variables

Time Series Data

Outliers and Missing Values

Excel Tables for Filtering, Sorting, and Summarizing

Conclusion

Finding Relationships Among Variables

Introduction

Relationships Among Categorical Variables

Relationships Among Categorical Variables and a Numerical Variable

Relationships Among Numerical Variables

Pivot Tables

An Extended Example

Conclusion

Probability and Decision Making Under Uncertainty

Probability and Probability Distributions

Introduction

Probability Essentials

Distribution of a Single Random Variable

An Introduction to Simulation

Distribution of Two Random Variables: Scenario Approach

Distribution of Two Random Variables: Joint Probability Approach

Independent Random Variables

Weighted Sums of Random Variables

Conclusion

Normal, Binomial, Poisson, and Exponential Distributions

Introduction

The Normal Distribution

Applications of the Normal Distribution

The Binomial Distribution

Applications of the Binomial Distribution

The Poisson and Exponential Distributions

Fitting a Probability Distribution to Data with @Risk

Conclusion

Decision Making Under Uncertainty

Introduction

Elements of a Decision Analysis

The Precision Tree Add-In

Bayes' Rule

Multistage Decision Problems

Incorporating Attitudes Toward Risk

Conclusion

Statistical Inference

Sampling and Sampling Distributions

Introduction

Sampling Terminology

Methods for Selecting Random Samples

An Introduction to Estimation

Conclusion

Confidence Interval Estimation

Introduction

Sampling Distributions

Confidence Interval for a Mean

Confidence Interval for a Total

Confidence Interval for a Proportion

Confidence Interval for a Standard Deviation

Confidence Interval for the Difference Between Means

Confidence Interval for the Difference Between Proportions

Controlling Confidence Interval Length

Conclusion

Hypothesis Testing

Introduction

Concepts in Hypothesis Testing

Hypothesis Tests for a Population Mean

Hypothesis Tests for Other Parameters

Tests for Normality

Chi-Square Test for Independence

One-Way Anova

Conclusion

Regression Analysis and Time Series Forecasting

Regression Analysis: Estimating Relationships

Introduction

Scatterplots: Graphing Relationships

Correlations: Indicators of Linear Relationships

Simple Linear Regression

Multiple Regression

Modeling Possibilities

Validation of the Fit

Conclusion

Regression Analysis: Statistical Inference

Introduction

The Statistical Model

Inferences About the Regression Coefficients

Multicollinearity

Include/Exclude Decisions

Stepwise Regression

The Partial F Test

Outliers

Violations of Regression Assumptions

Prediction

Conclusion

Time Series Analysis and Forecasting

Introduction

Forecasting Methods: An Overview

Testing for Randomness

Regression-Based Trend Models

The Random Walk Model

Autoregression Models

Moving Averages

Exponential Smoothing

Seasonal Models

Conclusion

Optimization and Simulation Modeling

Introduction to Optimization Modeling

Introduction

Introduction to Optimization

A Two-Variable Product Mix Model

Sensitivity Analysis

Properties of Linear Models

Infeasibility and Unboundedness

A Larger Product Mix Model

A Multiperiod Production Model

A Comparison of Algebraic and Spreadsheet Models

A Decision Support System

Conclusion

Optimization Models

Introduction

Worker Scheduling Models

Blending Models

Logistics Models

Aggregate Planning Models

Financial Models

Integer Programming Models

Nonlinear Programming Models

Conclusion

Introduction to Simulation Modeling

Introduction

Probability Distributions for Input Variables

Simulation and the Flaw of Averages

Simulation with Built-In Excel Tools

Introduction to the @Risk Add-in

The Effects of Input Distributions on Results

Conclusion

Simulation Models

Introduction

Operations Models

Financial Models

Marketing Models

Simulating Games of Chance

An Automated Template for @Risk Models

Conclusion

Bonus Online Material 2

Using the Advanced Filter and Database Functions

Importing Data into Excel

Introduction

Rearranging Excel Data

Importing Text Data

Importing Relational Database Data

Web Queries

Cleansing the Data

Conclusion

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