Subject 'Statistics'

Year:   2015/2016    2016/2017    2017/2018    2018/2019    2019/2020    

The course introduces the basic ideas of the collection, analysis, interpretation, presentation, and organization of data.
Short description of the course:
- population and sample, basic types of statistical variables, principles of study design and data collection;
- frequency distribution table, graphical representation of data, empirical distribution;
- numerical summary statistics (mean, median, standard deviation and s.o.), their calculating with statistical software, and interpretations;
- statistics probability, discrete and continuous random variables;
- common discrete and continuous probability distributions (uniform, binomial, Poisson binomial, normal, Student's t-distribution), their properties and graphical study;
- sampling distribution of sample means (Central Limit Theorem), estimation of population parameters (point and interval estimates);
- estimation and hypothesis testing about two populations;
- relationship between two variables (simple linear correlation, regression analysis).

The course introduces the basic techniques of handling data and analysing the results by using the methods of mathematical statistics and statistical software tools. Every person in today's society needs to have a basic understanding of data analysis and statistical concepts, in order to be able to think critically about the quantitative information we encounter every day, from opinion polls to headline news reports based on scientific studies.

By the end of this course, the student should
- be able to explain and apply principles of study design and data collection and be able to Identify the relevant population, sample, study units and variables;
- be able to produce and interpret graphical summaries of data (bar and pie charts, histograms, boxplots, scatterplots) and numerical summary statistics (mean, median, mode, range, standard deviation, variance, percentiles and s.o.);
- be able to compute simple probabilities of events and be familiar with common discrete and continuous probability distributions (uniform, binomial, Poisson binomial, normal, Student's t-distribution);
- be able to construct confidence intervals for population mean and to perform hypothesis tests about means of two populations;
- be able to describe graphically and numerically the relations between two variables using scatterplots, linear and Spearman's correlation coefficients and simple linear regression model;
- be familiar with basic statistical software tools (MS Excel, Geogebra or Mathcad).

The course consists of 32 contact hours: lectures, practical lessons, group study.
Independent work is about 46 academical hours: working through the lecture materials, solving practical exercises, e-learning, preparing for the tests.

1. Aruküla, H. Abiks majandusmatemaatika õppijaile VI, Matemaatiline statstika. TTÜ kirjastus, Tallinn, 1992.
2. Hiob, K. Matemaatiline statistika. Algkursus koolidele. Avita, Tallinn, 1995.
3. Käerdi, H. Statistika ja tõenäosusteooria alused. Sisekaitseakadeemia kirjastus, Tallinn, 1997, 1999.
4. Keres, K., Levin, A. Matemaatiline stastistika. Ülesannete kogu. TTÜ kirjastus, Tallinn, 2006.
5. Parring, A.-M., Vähi, M., Käärik, E. Statistilise andmetöötluse algõpetus. TÜ kirjastus, Tartu, 1997.
6. Prem S. Mann, Introductory Statistics, Wiley, NY, 2006.
7. Tammeraid, I. Tõenäosusteooria ja matemaatiline statistika, TTÜ kirjastus, Tallinn, 2004.
8. Yates, D., Moore, D., Starnes, D. The Practice of Statistics, Freeman, NY, 2002.
9. E-learning course materials at Moodle environment (http://ekool.tktk.ee).

During the course a student has to pass tests and to present homeworks. The tasks of the tests and homeworks are composed on the basis of the standard problems solved at the practical lessons and according to the topics from the course program. The number of tests and homework assignments during the course can be changed by the responsible lecturer.

Matemaatiline statistika - R. Timmermann
Statistika - K. Tamm
Statistika - M. Latõnina, E. Safiulina
Statistika - O. Labanova
Statistika - V. Retšnoi

2020: AE*  KT  LK  ME*  RR  TD  TK*  TK*  

2019: AT*  KT  LK  ME*  RR  RR  TD  TK*  TK*  TL  TT*  

2018: ET*  HE*  KK*  KT  LK  ME*  RG*  RR  RR  TD  TE*  TK  TK*  TL  TT*  

2017: ET*  HE*  KK*  KT*  ME*  RG*  RR  RT*  TD  TE*  TK  TL  TT*  

2016: ET*  HE*  KT*  ME*  RG*  RR  RT*  TD  TE*  TK  TL  TT*  

2015: ET*  HE*  KT*  ME*  RG*  RR  RT*  TD  TE*  TL  TT*  

* Optional subject