The emphasis of the course is on inferential statistics, i.e. the methods that permit one to make estimates and decisions about populations of measurements based on sample data.

Learning Outcomes

  1. Conduct appropriate tests for normality of data and evaluate probabilities associated with a Normal distribution

  2. Test hypotheses and construct confidence intervals for population parameters [mean(s), proportion(s), differences of means, differences of proportions, standard deviation]

  3. Test hypotheses for non-parametric data - Mann Whitney test, Wilcoxon Signed Rank and Rank Sum tests, Fisher's Exact Test

  4. Use chi-squared distribution to test for independence in contingency tables.

  5. Use MINITAB software to perform all tests, create confidence intervals and measure the power of a statistical test.

  6. Describe the main probability and non-probability sampling methods.

% Coursework 30%
% Final Exam 70%