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.
450 pages
