Programs

Course Content:

1. REGRESSION ANALYSIS :

Correlation coefficient - Simple linear Regression Models - Least squares estimation of the parameters - Coefficient of determination - Residual analysis - Multiple regression models - Modeling - Predictions - Stresses the use of the computer.

Assumptions of regression - variable selection - Prediction - Multicolinearity - Model Diagnostics - Dummy variables - Transformations - Logistic and Non-Linear Regression - Emphasizes use of computer predictions - Stresses use of the computer.

2. Statistical Quality Control :

Use of statistics for quality control and productivity improvement - Control chart calculations and graphing - Process control and specification - Sampling plans and reliability - Computer use will be stressed for performing calculations and graphing (MINITAB)

3. Design of Experiments :

experimental design as a method for organizing analysis procedures - Analysis of variance - Mathematical models and assumptions - Experimental units - Randomization - Replication - Blocking - Subdividing and Repeatedly measuring experimental units - Factorial treatment design - Nested, Latin squares and confounding - Extensions of the analysis of variance to cover general crossed and nested classifications and models that include both classificatory and continuous factors - Residual analysis - Stresses the use of the computer.