The following topics will be covered:
- Simple linear regression; intercept and slope; predictive and residual values. In the practical: basic SPSS techniques; entering data; simple scatter plots; linear regression.
- Linear regression continued; confidence intervals; correlation; relationship between regression and correlation. Practical.
- Multiple linear regression; comparing two means while correcting for prognostic variables. Practical.
- Multiple linear regressin; interaction, curvilinear relationships, residual plots. Practical.
- Logistical regression, introduction; contingency tables. Practical.
- Logistical regression, continued; interaction. Practical.
- Logistical regression, case-control studies. Practical.
- Statistical models; choice of variables; confounding; linearity; prediction models. Practical.
- Simple analysis of variance; f-test; multiple comparisons; contrasts; non-parametric analysis. Practical.
- Variance analysis of dependent data; analysis of cross-over research. Practical.