Statistics, Data Analysis, and Decision Modeling
James R. Evans, David L. Olson
327 pages, parution le 01/11/1999
Résumé
For a brief or modular course covering business statistics
and introductory topics in management science. Designed
specifically for today's shorter courses, often found in
MBA programs.
2. Displaying and Summarizing Data.
3. Random Variables and Probability Distributions.
4. Sampling and Statistical Analysis for Decision-Making.
5. Statistical Quality Control.
6. Regression.
7. Forecasting.
8. Selection Models and Risk Analysis.
9. Introduction to Optimization.
Appendix.
Index.
This text covers the basic concepts of business statistics, data analysis, and management science in a contemporary spreadsheet environment. The authors emphasize practical applications of the approaches to business decision making.
Features
- Concise approach?This book integrates fundamental concepts of business statistics and decision models in only nine chapters. The authors take a practical, non-mathematical approach.
-
- Covers only the major concepts and allows instructors to cover the material in the brief time they have.
- Practical applications?The authors emphasize applications throughout. In chapter one, the authors develop a comprehensive database, with marketing, financial, and production data already formatted on Excel worksheets. This comprehensive database is used throughout the text to give students hands-on experience in analyzing data for practical decision making.
-
- Students can see how real data are used and real decisions are made.
- Spreadsheet Environment?The emphasis is on using spreadsheets for data analysis and decision modeling. The book features Excel, and the Excel add-ins: PHSTAT, Crystal Ball, and TreePlan. The text will include boxed ?Notes? that contain procedural details for using these tools.
-
- Students gain familiarity with the tools they will use in their careers.
- Software Tools?PHSTAT, a collection of statistical tools that enhance the capabilities of Excel; a student version of Crystal Ball, the most popular commercial package for simulation and risk analysis; and TreePlan, a decision analysis add-in, are included on the CD-ROM packaged with the book for free.
-
- The software needed for the course is provided free with the text.
- Free Student CD-ROM?Contains PHSTAT, Crystal Ball, TreePlan, the comprehensive database files, and additional data files for problems and exercises.
-
- Provides students with the software needed to help solve some of the exercises in the text.
Contents
1. Data and Business Decisions.
The Importance of Data for
Decision Making. Types and Sources of Business Data.
Measurement and Statistics. Decision Models. Using
Microsoft Excel. Summary.Questions and Problems.
2. Displaying and Summarizing Data.
Displaying Data with
Charts and Graphs. Descriptive Statistics. Visual Display
of Statistical Measures. Statistical Relationships. Case
Study: Using Descriptive Statistics for the Malcolm
Baldrige National Quality Award. Summary. Questions and
Problems.
3. Random Variables and Probability Distributions.
Basic Concepts. Discrete
Probability Distributions. Continuous Probability
Distributions. Random Sampling From Probability
Distributions. Summary. Questions and Problems. Appendix:
Introduction to Crystal Ball.
4. Sampling and Statistical Analysis for Decision-Making.
Statistical Sampling.
Statistical Analysis of Sample Data. Estimation. Hypothesis
Testing. ANOVA: Testing Differences of Several Means.
Chi-Square Test for Independence. Summary. Questions and
Problems. Appendix: Distribution Fitting.
5. Statistical Quality Control.
The Role of Statistics and
Data Analysis in Quality Control. Statistical Process
Control. Control Charts for Attributes. Statistical Issues
in the Design of Control Charts. Process Capability
Analysis. Summary. Questions and Problems.
6. Regression.
Simple Linear Regression.
Measuring Variation About the Regression Line. Regression
as Analysis of Variance. Assumptions of Regression
Analysis. Applications of Regression Analysis to Investment
Risk. Multiple Linear Regression. Building Good Regression
Models. Regression with Ordinal and Nominal Independent
Variables. Regression Models with Nonlinear Terms. Summary.
Questions and Problems.
7. Forecasting.
Qualitative and Judgmental
Methods. Statistical Forecasting Models. Regression Models.
The Practice of Forecasting. Summary. Questions and
Problems. Appendix: CB Predictor.
8. Selection Models and Risk Analysis.
Decision Criteria and
Selection. Monte-Carlo Simulation for Risk Analysis.
Applications of Monte-Carlo Simulation. Case Study:
Simulation and Risk Analysis in New Product Screening at
Cinergy Corporation. Summary. Questions and Problems.
Appendix: Additional Crystal Ball Options.
9. Introduction to Optimization.
Constrained Optimization.
Types of Optimization Problems. Spreadsheet Optimization.
Solving Linear Optimization Models. Solving Integer
Optimization Models. Solving Nonlinear Optimization Models.
Risk Analysis of Optimization Results. Combining
Optimization and Simulation. Summary. Questions and
Problems.
Appendix.
The Standardized Normal
Distribution. The Cumulative Standard Normal Distribution.
Critical Values of t. Critical Values of
F.
Index.
L'auteur - James R. Evans
University of Cincinnati
L'auteur - David L. Olson
Texas A&M University
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Prentice Hall |
| Auteur(s) | James R. Evans, David L. Olson |
| Parution | 01/11/1999 |
| Nb. de pages | 327 |
| Format | 20 x 25 |
| Couverture | Broché |
| Poids | 649g |
| Intérieur | Noir et Blanc |
| EAN13 | 9780130205452 |
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