Syllabus
1. Descriptive statistics.
2. Frequencies and probabilities, independence, Bayes theorem.
3. Random variable and its distribution, characteristics of random variables.
4. Random sample, population, parameter estimation, hypotheses testing.
5. One sample tests.
6. Two sample tests.
7. Analysis of variance.
8. Regression, correlation.
9. Contingency tables.
Annotation
Data analysis principles. Descriptive statistics.
Introduction to inferential statistics (statistical hypothesis, statistics, significance level, p value, confidence interval). One/two independent samples procedures.
Regression. Contingency tables.