2. Testing Hypothesis      Chapter 9
 Illustration of Testing an hypothesis about an assumption about a state of the world (decision problem solving); Basic concepts of Hypothesis Testing; One sample test of a amen; large samples; of error, i.e., Type I and II; Measuring the probability of a Type II error; evaluation of a test of hypothesis - The Operating Characteristic and/or Power Curve; One sample test of a Population Proportion, large sample and small samples; Use of T-distribution in small sample tests for the mean; Use of statistical software, i.e., the T-Test and Z Test command.  What is the appropriate sample size for the test about a mean - a proportion; Application to Total Quality Management - The Deming  Approach.

3. The Comparative Experiment      Chapter 10
 Testing the difference in mean of two populations, large sample designs; Use of T-distributions for test involving small sample; Testing the difference in proportions of two populations; Use of Statistical Software; Choosing the right model for decision making - evaluating the assumptions of the decision model.

4. Regression and Correlation Analysis     Chapter 14
 Introduction, relationships and the Scatter diagram (use of statistical software); Aims of Regression and Correlation; the Linear Regression Models, its assumptions; The Sample Regression Line; The Method of Least Squares; Characteristics of Least Squares Estimates; The Standard Error of Regression (estimate); Estimators of (1) the conditional mean and (2) an individual value of Y; the Coefficient of Determination; Coefficient; Inference Concerning the Intercept, A; Application to Statistical Cost Functions; Application to a Stock’s Beta; Use of Statistical  Software; Evaluation of Model Error by Statistical Software.

5. Business and Economic Time Series    Chapter 18
 Introduction; The Classical Time Series Model and its Components; The least squares linear trend model; Estimation of a nonlinear Trend model-meaning of derivative of model; Method of Moving Averages; Exponential Smoothing as an example of a moving average; Seasonal Index, Ration-To-Moving-Average Method; Calculation of Seasonal Variation, Dummy Variable (Regression) Method; Cyclical Variation; Elementary Forecasting Techniques; Advanced techniques introduction; Use of Statistical Software; Introduction to the Multilinear Model for Decision Making and Forecasting.

6. Index Numbers      Chapter 17
 What do index numbers measure and why are they so important; Unweighted Index Numbers; Weighted Index Numbers;  Why price and quality index numbers are statistical opposites;  Other weighting schemes; Chain Index Numbers; Examples; The Consumer Price Index, the Producer Price Index; the Index of Industrial Production; Use of Statistical Software.

7. How Top Managers Improve Product and Service Quality by the Use of Statistical Methods?       Chapter 20
 Emphasis on the Quality Movement-Deming, Shewhart, Juran and Taguchi; What Causes Lack of Uniformity; Reduced Emphasis on Inspection; Statistical Process Control; The Control Chart; Mean and Range Charts; Mean and Standard Deviation Charts; the C Chart; Use of statistical software;  Experiment Design and Quality Improvement; How to get statistical methods accepted?

8. Experimental Designs-Comparing More Than Two Populations. Chapter 13
 Design of Industrial Experiments; the Analysis of Variance Model; the F Distribution; Analysis of a Completely Randomized Design; One Way and Two Designs;  Use of Statistical Software.

9. Chi-Square and Nonparametric Designs   Chapters 11 and 12
 The Chi-Square Distribution and Testing Model; Test of differences among proportions; Contingency Tables; Statistical Software Applications; Tests of Goodness of Fit; Testing for Normality; Tests and Confidence Intervals concerning the variance; The Sign Test; Mann-Whitney Test; Runs Test; Non parametric tests, and evaluation of its benefits and costs.

10. Decision  Analysis and Theory    Chapter 22
 Decision Matrix and trees; Utility, Monetary Equivalents and Expected Monetary Value; Prior Analysis, Sampling and Preposterior  Analysis; Evaluation after Sampling or Posterior Analysis; Opportunity Loss; Critical Thinking; the Evaluation of the Decision; Applications to Pricing Inventories, and Capital Budgeting; Use of Statistical Software.

Texts to Purchase
1.  Statistics for Business and Economics, By Anderson, Sweeney and Williams
 (8th Ed.), West, 1999
2.  The Student Edition of  Minitab for Windows,
You will have 3 examinations and extensive assignments using Minitab.