Hypothesis Tests and Confidence Intervals for the difference between two population means or proportions using independent samples and using paired data. Hypothesis testing for proportions and independence. Testing the fit for a population model. The simple linear regression model. Inferences based on the estimated regression line. Inferences on the population correlation. Checking model adequacy. Single factor ANOVA. Multiple comparisons. Randomised block experiment. Two-factor ANOVA. Distribution free procedures. One and two way frequency tables.

On completion of this module students should be able to compute the equation of the least squares line. They should be able to compute confidence intervals and prediction intervals from the least squares estimates. They should be able to perform some basic diagnostic checks on the performance of regression models. They should be able to conduct single factor and two factor analyses of variance. They should understand the problems associated with multiple comparisons and be able to compute appropriate confidence intervals. They should be able to perform a hypothesis test and compute a confidence interval for the difference between two population means or proportions using independent samples and using paired data. They should be able to conduct some basic non-parametric hypothesis tests and should be able to conduct some basic goodness of fit tests