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307591 (v.1) Data Evaluation and Experimental Design 103
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
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| 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. |
Availability
| Year | Location | Period | Internal | Area External | Central External | | 2004 | Bentley Campus | Semester 1 | Y | | | | 2004 | Bentley Campus | Semester 2 | Y | | |
Area
External | refers to external course/units run by the School or Department, offered online or through Web CT, or offered by research. |
Central
External | refers to external course/units run through the Curtin Bentley-based Distance Education Area |
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