Content (Syllabus outline)
Introduction. Basic statistical notions. Data collection.
Descriptive statistics. Relative numbers. Quantiles. Measures of central tendency. Measures of variability and diversity.
Statistical inference. Probability distributions (normal, binomial). Sampling distribution for mean, variance, proportion. Parameter estimation (point and interval). Hypothesis testing for: one sample, two (independent, dependent) samples for mean and Bernoulli probability.
Bivariate analysis. Simple linear regression. Correlation coefficient. Rang correlation coefficient. Nonlinear models which can be linearized.
Contingency tables. Hi-square statistic.
Advanced statistical methods: a brief overview.
Prerequisites
Requirements for enrolment:
- course enrolment.
Terms of Prerequisites:
- completed exam in computer lecture room is the prerequisite for the written exam.