Data Analysis and Decision Making

Name: Data Analysis and Decision Making
Price: 5.7 USD
Availability: InStock
ISBN: 9780538476126

ISBN-10: 0538476125

ISBN-13: 9780538476126

Edition: 4th 2011

Authors: S. Christian Albright, Wayne Winston, Christopher Zappe

List price: $333.95

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Book details

List price: $333.95
Edition: 4th
Copyright year: 2011
Publisher: Cengage South-Western
Publication date: 10/12/2010
Binding: Hardcover
Pages: 1080
Size: 8.25" wide x 10.00" long x 1.75" tall
Weight: 4.334

S. Christian Albright received his B.S. degree in mathematics from Stanford in 1968 and his Ph.D. in operations research from Stanford in 1972. Since then, he has been teaching in the Operations and Decision Technologies Department in the Kelley School of Business at Indiana University. He has taught courses in management science, computer simulation, and statistics to all levels of business students: undergraduates, MBAs, and doctoral students. His current interest is in spreadsheet modeling, including development of VBA applications in Excel. Dr. Albright has published more than 20 articles in leading operations research journals in the area of applied probability as well as a number of…

Wayne L. Winston is a professor of Decision Sciences at Indiana University's Kelley School of Business and the recipient of more than 30 teaching awards. For the past 20 years, Wayne has also taught Fortune 500 companies how to use Excel to make smarter business decisions. He has written 15 books on Excel, management science, and mathematics in sports.



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