Data analysis for science

This unit is designed to develop an understanding of some of the most widely used methods of statistical data analysis, from the viewpoint of the user, with an emphasis on planned experiments. You will become familiar with at least one standard statistical package. Topics covered include: parametric and nonparametric procedures to compare two independent and matched samples; review of simple linear regression; multiple linear regression - analysis of residuals, choice of explanatory variables; model selection and validation; nonlinear relationships; introduction to logistic regression; basic principles of experimental design; one-way and two-way analysis of variance models; planned and multiple comparison techniques; power and sample size considerations in design; usage of some available statistical packages including Minitab and/or SPSS, data preparation, interpretation of output.