Statistics, Data Analysis and Decision Modeling and Student CD-ROM

(NOTE: Each chapter begins with an Introduction and includes Questions and Problems.)

1. Data and Business Decisions.


Statistical Thinking in Business. Data in the Business Environment. Sources and Types of Data. Populations and Samples. Decision Models. Using Microsoft Excel. Working with Data in Excel. Case: The Tracway Balanced Scorecard.



2. Displaying and Summarizing Data.


Displaying Data with Charts and Graphs. Contingency Tables and Cross-Tabulations. Descriptive Statistics. Measures of Dispersion. Calculations for Grouped Data. Coefficient of Variation. Measures of Shape. Excel's Descriptive Statistics Tool. Data Profiles and Proportions. Visual Display of Statistical Measures. Statistical Relationships. Case: Descriptive Statistical Analysis of Tracway Data.



3. Random Variables and Probability Distributions.


Basic Concepts. Random Variables. Probability Distributions. Expected Value and Variance of a Random Variable. Discrete Probability Distributions. Continuous Probability Distributions. Other Useful Distributions. Monte-Carlo Methods in Statistics. Sampling Distributions and Sampling Error. Case: Probability Modeling for Tracway Quality Measurements.



4. Sampling and Statistical Inference.


Statistical Sampling. Statistical Analysis of Sample Data. Estimation. Interval Estimates. Confidence Intervals for the Mean. Confidence Intervals for Proportions. Confidence Intervals and Sample Size. Additional Types of Confidence Intervals. Hypothesis Testing. One Sample Hypothesis Tests. Two-Sample Hypothesis Tests. ANOVA: Testing Differences of Several Means. Non Parametric Hypothesis Tests. Distribution Fitting: An Application of Hypothesis Testing. Case: Statistical Inference for Tracway.



5. Regression Analysis.


Simple Linear Regression. Measuring Variation About the Regression Line. Regression as Analysis of Variance. Assumptions of Regression Analysis. Application of Regression Analysis to Investment Risk. Multiple Linear Regression. Building Good Regression Models. Regression with Categorical Independent Variables. Regression Models with Nonlinear Terms. Case: Regression Analysis for Tracway.



6. Forecasting.


Qualitative and Judgmental Methods. Indicators and Indexes. Statistical Forecasting Models. Forecasting Models for Stationary Time Series. Forecasting Models with Linear Trends. Models for Time Series with Trend and Seasonal Components. CB Predictor. Regression Models. The Practice of Forecasting.



7. Statistical Quality Control.


The Role of Statistics and Data Analysis in Quality Control. Statistical Process Control. Analyzing Control Charts. Control Charts for Attributes. Statistical Issues in the Design of Control Charts. Process Capability Analysis. Case: Quality Control at Tracway. References.



8. Risk Analysis and Monte-Carlo Simulation.


Risk Analysis. Monte-Carlo Simulation with Crystal Ball. Additional Crystal Ball Modeling and Analysis Options. Applications of Monte-Carlo Simulation.



9. Systems Simulation Modeling and Analysis.


System Simulating Modeling Approaches. Simulating Inventory Systems Using Activity Scanning. Simulating Waiting Line Systems Using Process-Driven Models. Event-Driven Simulation Models. An Event-Driven Inventory Simulation Model. Entities and Attributes. Continuous Simulation Modeling. Case: Tracway Production/Inventory Planning. References.



10. Selection Models and Decision Analysis.


Decisions Involving a Single Alternative. Decisions Involving Non-Mutually Exclusive Alternatives. Decisions Involving Mutually Exclusive Alternatives. Decisions Involving Uncertainty. Case: A Tracway Decision Problem. References.



11. Optimization Modeling.


Constrained Optimization. Linear Optimization Models. Spreadsheet Implementation of Linear Programming Models. Integer Optimization Models. Nonlinear Optimization. Case: Distribution Center Location for Tracway.



12. Solving and Analyzing Optimization Models.


Using Spreadsheet Models for Optimization. Solving Linear Optimization Models. Solving Integer Optimization Models. Solving Nonlinear Optimization Models. Risk Analysis of Optimization Results. Combining Optimization and Simulation. Case: Distribution Center Location for Tracway.