Statistical Methods in Economics
Description
Šio kurso tikslas yra suteikti studentams tikimybių teorijos ir statistikos teorinių ir praktinių žinių. Kursas suteiks pagrindines žinias apie tikimybių teoriją, diskrečiuosius ir tolydžiuosius atsitiktinius dydžius ir jų skirstinius, populiaciją ir imtį, imčių sudarymo metodus, aprašomąsias statistikas, taškinius ir intervalinius įverčius, hipotezių tikrinimą, neparametrinius kriterijus, regresinės analizės metodus.
Aim of the course
The main goal of the course is to present some fundamentals of probability theory and statistics. The content includes: classical and statistical definition of probability; conditional probability and independence; random va-riable; probability distribution function; characteristics of random variables; limit theorems; general population and sample; visualizing data; descriptive statistics; estimation of population parameters under empirical charac¬teristics of sample; point estimation of parameters; interval estimation; statistical hypothesis testing; nonparametric criteria; basics of regression analysis.
Prerequisites
Mathematics
Course content
1. Random events.
2. Probability definitions.
3. Conditional probability and independence.
4. Total probability and Bayes’s Rule. Bernoulli scheme.
5. Random variable and distribution function.
6. Discrete and continuous random variables and distributions.
7. Random variable characteristics.
8. Population and sample.
9. Data grouping. Empirical data characteristics.
10. Graphical data presentation.
11. Point estimates. Confidence intervals.
12. Basic concepts of hypothesis testing.
13. Testing parametrical hypothesis.
14. Non-parametrical criteria.
15. Simple regression.
Assesment Criteria
The student is able to recognize and describe the concepts of probability theory, able to solve probability theory exercises, construct random variable distribution.
The student is able to perform initial statistical analysis, calculate main statistical characteristics.
The student is able to present data and its characteristics graphically.
The student is able to construct statistical hypothesis and perform hypothesis testing.
The student is able to build regression equation and estimate parameters.
