1) Statistical packages (how to use).
2) Brief overview of (a) the principles of statistical inference and (b) inference about means, proportions and variances (confidence intervals and hypothesis tests for a population mean, proportion or variance and for comparing two population means, proportions or variances; Analysis of variance and multiple comparisons tests ; Goodness-of-fit test; Chi-Square test of independence).
3) How to apply checks for method’s assumptions (tests for Normality, tests for comparing variances, normal probability plots, residuals plots, etc.).
4) Non-parametric tests (Sign test, Mann-Whitney test, Wilcoxon test, Kruskal-Wallis test, Friedman test, etc.).
5) Regression analysis (simple linear regression and correlation; multiple regression; logistic regression).
6) Diagnostic tools for checking the regression assumptions (residuals plots, etc.); data transformations.
1. Κούτρας, Μ. Β. και Ευαγγελάρας Χ., Ανάλυση Παλινδρόμησης-Θεωρία και Εφαρμογές, Εκδόσεις Σταμούλη, 2010.
2. Watt, T. A., McCleery, R. H. and Hart, T., Introduction to Statistics for Biology, Chapman and Hall/CRC, Third Edition, 2007.
3. Zar, J. H., Biostatistical Analysis, Prentice Hall, Fifth Edition, 2010.
