LV EN RU DE FR

Statistical Methods and Applications

Course developer

Prior knowledge

VidZ5038, Statistical Methods

Course abstract

The study course aims to master the methods of mathematical statistics thoroughly, emphasizing their practical significance in environmental, water and land engineering research. The study course continues to acquaint students with the methods of mathematical statistics. Students learn variance analysis, correlation, regression analysis, time series analysis and spatial data analysis, as well as method selection conditions and correct interpretation of results.

Learning outcomes and their assessment

After the study course, the student:
• knows and understands the application of variance, correlation, regression analysis, time series analysis and spatial data analysis (tests 1 and 2);
• is able to apply the acquired methods of statistical analysis in solving the research tasks (tests 1 and 2)
• is able to practically apply the acquired statistical methods in data analysis (laboratory works);
• can analyze and systematize data processing results and critically evaluate them in a specific field of study (homework).

Course Content(Calendar)

1. Application of statistical methods in environmental, water and earth engineering [L 1h, P 1h].
2. Examples of application of variance analysis [L 1h, P 1h].
3. Use of correlation analysis [L 1h, P 1h].
4. Application of single-factor linear regression analysis [L 1h, P 1h].
Test 1: Use of variance and regression analysis.
5. Basics of nonlinear regression [L 2h, P 2h].
6. Use of multifactor regression analysis [L 2h, P 2h].
7. Methods of time series analysis [L 2h, P 2h].
8. Application of statistical methods for spatial data analysis [L 2h, P 2h].

Requirements for awarding credit points

Formal test with a grade. The cumulative grade consists of:
• 2 tests (includes questions on the theory of acquired topics and solving exercises);
• Homework (practical data research task).
All works must be written and submitted on time.
Tests can be written only at the specified time and once.

Description of the organization and tasks of students’ independent work

Homework: Application of regression models in various researches of environmental, water and earth engineering (volume at least 5 pages, submitted electronically, presentation - in the auditorium).

Criteria for Evaluating Learning Outcomes

The study course evaluation depends on the cumulative evaluation of the study course tests and homework: Test 1: (40%). Test 2: (40%). Homework: research of the application of statistical methods, preparation of a report submitted in the e-learning environment, presentation of work results (20%).

Compulsory reading

Arhipova I., Balina S. Statistika ekonomikā un biznesā. Risinājumi ar SPSS un MS Excel: mācību līdzeklis. Rīga: Datorzinību centrs, 2006. 362 lpp.
Smotrovs J. Varbūtību teorija un matemātiskā statistika II. Rīga: Zvaigzne ABC, 2007. 136 lpp.
Brandt S. Data analysis: statistical and computational methods for scientists and engineers. 4th edition. Cham: Springer, 2014. 523 p.

Further reading

Mac Berthouex P., Brown L.C. Statistics for environmental engineers. Boca Raton etc.: Lewis Publishers, 2002. 489 p.
Shaw P. J. A. Multivariate Statistics for the Environmental Science. Wiley, 2009. 244 p.
Helsel D.R., Hirsch R.M. Statistical Methods in Water Resources Techniques of Water Resources Investigations. U.S.: Geological Survey, 2002. 522 p.
Gilbert R.O. Statistical Methods for Environmental Pollution Monitoring. John Wiley&Sons, 1987. 336 p.
Gibbons R.D., Coleman D.E. Statistical methods for detection and quantification of environmental Contamination. John Wiley&Sons, 2001. 384 p.
Chun Y., Griffith Daniel A. Spatial Statistics and Geostatistics. SAGE, 2013. 200 p
Schabenberger, O., Gotway, C. Statistical Methods for Spatial Data Analysis. Chapman &Hall/CRC, 2005. 512 p.

Periodicals and other sources

1. Official Statistics Portal [online] Available: https://stat.gov.lv/en
2. Eurostat [online] Available: https://ec.europa.eu/eurostat/web/main
3. FAOSTAT [online] Available: https://www.fao.org/faostat/en/#home
4. Science direct [online] Available: https://www.sciencedirect.com/
5. Scopus [online] Available: https://www.scopus.com/home.uri

Notes

The course is compulsory for the academic master's study programme "Environmental, Water and Land Engineering" full-time studies