307591 (v.1) Data Evaluation and Experimental Design 103

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Area:	Department of Mathematics and Statistics
Contact Hours:	3.0
Credits:	12.5
Lecture:	1 x 2 Hours Weekly
Tutorial:	1 x 1 Hours Weekly
Anti Requisite(s):	7149 (v.7) Principles of Statistics 101 or any previous version 10925 (v.3) Principles of Statistics 103 or any previous version 307590 (v.1) Data Evaluation and Experimental Design 101 or any previous version
Designed for students with TEE Applicable Mathematics. Regression Analysis. Simple linear regression - measures of model adequacy, residual analysis, transformations, Inference for slope and intercept. Confidence and prediction intervals for future responses. Multiple linear regression - estimation of model parameters, inference regarding model parameters and predictions, ANOVA, regression diagnostics, variable selection and model building. Non Parametric Methods. Introduction to non parametric analysis. Non parametric tests - Sign test, Signed-rank test, Rank-sum test, Runs test. Kruskal Wallace test, Rank correlation coefficient Checking distributions - Q-Q plots and Kolmogorov Smirnov.