Statistics

Measuring and measuring scales. Data collection methods. Diagrams. Measures of central tendency and variation. Probability distributions (binomial, Poisson, exponential and normal distribution). Sampling and inferences based on a sample. Hypothesis testing (t-test, chi-square test, F-test, analysis of variance). Correlation and regression analysis. Time series: elementary analysis, smoothing, analysis of seasonality, forecasting. Index numbers.

NB! This course will take place in spring semester 2024/2025 which starts on 3rd of February and ends on 16th of June (you can find that information under Start date section). The real course start and end dates will be announced at the beginning of February at the latest.

After accomplishing the course the student:

• uses descriptive and inferential statistics terms and methods correctly;
• formulates research questions in a justified manner and select appropriate data analysis methods accordingly;
• analyzes statistical data using software, applying descriptive and inferential statistical methods;
• interprets and critically evaluate datasets and the results of statistical data analysis;
• synthesizes and articulates conclusions based on data analysis results.

Final assessment can consist of one test/assignment or several smaller assignments completed during the whole course. After declaring a course the student can re-sit the exam/assessment once. Assessment can be graded or non-graded. For specific information about the assessment process please get in touch with the contact person of this course. For specific information about grade transfer please contact your home university

• Sauga, A. Statistika õpik majanduseriala üliõpilastele. Tallinn: TTÜ, 2020.
• Main textbook: Statistics for Business and Economics, by McClave, Benson,and Sincich,12thedition, Pearson.
• Alternative textbook: Statistics for Business and Economics, by Anderson, Sweeney, and Williams, West Publishing Company

lectures, practices