Marko Pahor PhD, Full Professor
Chair: 88/IV
E-mail:
Phone: (051) 355 132
Courses
Study Programs in English
Statistical analysis (UNDERGRADUATE study program)
The course deals with applied statistics, therefore it emphasizes those skills that will enable students to independently evaluate and analyze real data through sampling.
Course content
Sampling theory: sample and sampling distribution. Descriptive versus inferential statistics;
Inferential statistics: Confidence interval estimation of means and proportions. Large and small samples. Choosing the sample size and sample size estimation. Fundamentals of hypothesis testing. Hypothesis test for mean and for proportion. Chi-square statistics. Regression analysis.
Course content
Sampling theory: sample and sampling distribution. Descriptive versus inferential statistics;
Inferential statistics: Confidence interval estimation of means and proportions. Large and small samples. Choosing the sample size and sample size estimation. Fundamentals of hypothesis testing. Hypothesis test for mean and for proportion. Chi-square statistics. Regression analysis.
Statistics for business and economics
Expected learning outcomes
After passing the exam, students will be able to:
- Identify and explain the basic concepts of statistics and probability
- Analyze statistical data using descriptive statistics methods, apply probability and estimate population parameter based on a sample
Course content
Definition of statistics. Basic concepts. Statistical data. Data editing and tabulation. Statistical graphics. Software support for statistical analysis. Data analysis using descriptive statistics methods. Time series analysis. Definition of time series. Dynamics indicators. Indices. Basic concepts of probability. Random variable and its properties. Selected discrete and continuous probability distributions. Central limit theorem. Sampling distributions. Estimation of selected population parameters. Estimation of the difference of selected parameters of two populations. Determining the minimum required sample size
After passing the exam, students will be able to:
- Identify and explain the basic concepts of statistics and probability
- Analyze statistical data using descriptive statistics methods, apply probability and estimate population parameter based on a sample
Course content
Definition of statistics. Basic concepts. Statistical data. Data editing and tabulation. Statistical graphics. Software support for statistical analysis. Data analysis using descriptive statistics methods. Time series analysis. Definition of time series. Dynamics indicators. Indices. Basic concepts of probability. Random variable and its properties. Selected discrete and continuous probability distributions. Central limit theorem. Sampling distributions. Estimation of selected population parameters. Estimation of the difference of selected parameters of two populations. Determining the minimum required sample size
