1. Population and sample, random sample, frequencies
2. Division of data into classes (procedure and reason for doing so), histogram
3. Moment and quantile characteristics
4. The theorem on a single drawing from normal distribution and its use
5. The theorem on two drawings from normal distribution and its use
6. Hypothesis testing – general procedure, type I and II errors in testing
7. F-test, t-tests (all steps taken in the test)
8. Correlation analysis (the r coefficient and its testing, correlation index, condition for use, properties)
9. Multivariate regression analysis (principal matrix formulae)
10. Spearmann’s correlation coefficient, contingency tables
11. Point estimation of
12. Interval estimation of
13. Test of normality (skewness and kurtosis of normal distribution, Shapiro-Wilk test and its table of critical values)
14. Testing of outliers (Grubb’s test, Box Plot), tests of data independence (sign test).
2. Division of data into classes (procedure and reason for doing so), histogram
3. Moment and quantile characteristics
4. The theorem on a single drawing from normal distribution and its use
5. The theorem on two drawings from normal distribution and its use
6. Hypothesis testing – general procedure, type I and II errors in testing
7. F-test, t-tests (all steps taken in the test)
8. Correlation analysis (the r coefficient and its testing, correlation index, condition for use, properties)
9. Multivariate regression analysis (principal matrix formulae)
10. Spearmann’s correlation coefficient, contingency tables
11. Point estimation of
12. Interval estimation of
13. Test of normality (skewness and kurtosis of normal distribution, Shapiro-Wilk test and its table of critical values)
14. Testing of outliers (Grubb’s test, Box Plot), tests of data independence (sign test).