Lecture: 3 hours

Exercise: 1 hour

Prerequisites: Introduction to Probability

 

Goal: The aim of the course is to represent the theoretical and practical background

for planning experiments and statistical analysis. It includes: theoretical statistics,

sampling and sample, parameter and point estimation, confidence interval estimation,

tests of hypothesis, simple linear regression and multiple linear regression.

Topics:

1. Simple random sampling

2. Properties of sample mean, sample variance and sampling fraction

3. The notion of statistic, point estimators, estimation methods: method of moments,

maximum likelihood method

4. Estimators' properties, unbiased estimators, efficiency and consistency

5. Confidence intervals, confidence interval of the mean and of the proportion

6. Size of sample

7. Distributions t,F,χ 2

8. Tests of hypotheses, type I and type II errors

9. Tests of hypotheses on the mean, when variance known and when variance

unknown

10. Tests of hypotheses on the variance

11. Tests of hypotheses on the equality of two means

12. Tests of hypotheses on two proportions

13. χ 2 tests

14. Introduction to ANOVA

15. Introduction to simple linear regression