Description:
Regression, correlation, analysis for variance (ANOVA), design of experiments, and their applications in Industrial Engineering.
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Topics:
1. Simple Linear Regression and Correlation
a. Empirical Models
b. Modeling Linear Relationships: The Least-Squares Approach
c. Correlation: Estimating the Strength of a Linear Relationship
d. Hypothesis Tests in Simple Linear Regressions
e. Prediction of New Variables
f. Adequacy of the Regression Model
2. Multiple Linear Regression
a. Multiple Linear Regression Model
b. Hypothesis Tests in Multiple Linear Regression
c. Prediction of New Observations
d. Model Adequacy Checking
3. Design and Analysis of Single-Factor Experiments
a. Completely Randomized Design
i. Analysis of Variance (ANOVA)
ii. Multiple Comparisons following ANOVA
iii. Residual Analysis and Model Checking
iv. Determining Sample Size
b. Random and Fixed Effects Experiments
i. Fixed vs. Random Factors
ii. ANOVA and Variance Components
c. Randomized Complete Block Design
i. Design and Statistical Analysis
ii. Multiple Comparisons
iii. Residual Analysis and Modeling
d. Latin-Square Design and Graeco-Latin Square Design
i. Design and Statistical Analysis
ii. Multiple Comparisons
iii. Residual Analysis and Modeling
4. Design of Experiments with Several Factors
a. Random and Mixed Models
b. General Factorial Design
c. Two-Factor Factorial Experiments
i. Statistical Analysis
ii. Model Adequacy Checking
d. 2K Factorial Design
i. Single Replicate
ii. Addition of Center Points
iii. Blocking and Cofounding
iv. Fractional Replication
e. Response Surface Methods
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