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STATISTICS,DATA ANALYSIS AND DECISION MODELING


EVANS J. OLSON D.

wydawnictwo: PRENTICE HALL , rok wydania 2000, wydanie I

cena netto: 260.00 Twoja cena  247,00 zł + 5% vat - dodaj do koszyka

Statistics, Data Analysis, and Decision Modeling, 1/e

James R. Evans , University of Cincinnati
David L. Olson , Texas A&M University
Published November 1999 by Prentice Hall Business Publishing

Copyright 2000, 329 pp. Paper Bound w/CD-ROM ISBN 0-13-020545-1

CD-ROM included

Summary

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.

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.


Table of 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.

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