LECTURE SLAIDS (in Estonian)

• Nature of statistics; data and traits; population and sample [slaids]
• Descriptive statistics [slaids]
   
• Theoretical background - theoretical distributions, estimation, accuracy of estimates (tolerance and confidence interval, standard error) [slaidid]
• Hypothesis testing; comparison of two groups - t-tests and nonparametric tests [slaids]
   
• Relationships between numerical variables - correlation and regression analyses [slaids]
   
• Relationships between categorical variables - chi-square test, Fisher exact test; odds ratio [slaids]
• Multiple comparisons. Analysis of variance, analysis of covariance[slaids]
   
• General linear models (models equations, contrasts, least square means, random factors, mixed models) [slaids]
   
• Analyses of binary traits (logistic regression, ROC-curves) [slaids]
• Multivariate analyses (cluster analysis, principal components analysis, ...) [slaids]
   
• Power analysis, sample size calculation [slaids]
• Statistics in scientific papers [slaids]