Statistical Analysis (PD)

- Become familiar with and upgrade basic statistical methods.
- Obtain basic knowledge about sampling, parameter estimation and analysis of relationship between variables.
- Develop skills and ability to use statistical analysis software.
- Develop the ability of critical thinking and evidence-based inference.

- Introduction: statistical terminology and basic descriptive statistics.
- Probability distributions: basic concepts, normal distribution, standardized normal distribution.
- Sampling (simple random sampling): random unit selection, sample estimate, estimator, distribution of sample estimates.
- Confidence intervals.
- Different types of sampling methods.
- Hypotheses testing: null and alternative hypothesis, type 1 and type 2 errors, hypothesis testing procedure about a population.
- Testing hypothesis: about mean (and the difference between two means and equality of more means), about variance (and equality of variances), about proportion.
- Correlation, simple and multiple linear regression, regression model
building.
- Relationship between categorical variables.
- Non-parametric tests.
- Time series analysis: basic concepts, linear and exponential trend function, periodical component.