436-341 Applied Statistics

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Objectives:

On completion, students will be able to apply techniques of regression and analysis of variance to practical engineering problems, to design and analyse experiments and will have acquired the basic knowledge necessary to determine optimum operating conditions.

Content:

Experimental design: experimental error, reliability. Sampling and testing methods: randomised block, Latin square, factorial, 2k and fractional designs, response surface methodology designs. Design problems associated with human involvement. Data analysis methods: single and multiple factor regression, identification of outliers, residuals, regression with variance on both variables; analysis of variance, single factor and factorial designs, random factors, nesting, interpretation of interaction. Post-hoc testing. Power analysis. Use of Minitab for solution of problems.

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