Name of the advanced training program

Statistical analysis and data processing on a computer

Name of the department

Department of Modern Educational Technologies

Form of education

full-time

Number of hours

72 hours

Full name of lecturers, academic degree and rank

Maksimov S.I., Ph.D., Associate Professor;

Zaitseva E.M., PhD , Associate Professor;

Learning objectives

familiarization with the basic models and methods of applied statistics, with preliminary processing of statistical data, as well as mastering practical skills in working with Excel, Gnumeric , and SPSS packages to solve scientific and practical problems in subject areas

Brief summary, content of the advanced training program

Introduction to Applied Statistics (6 hrs):

- tasks and methods of variance analysis;

- one-factor analysis: significance and explanatory power of the model;

- multiple comparisons;

- two-factor analysis, interaction of factors, significance of effects.

Computer statistical analysis and data processing using Excel, Gnumeric , SPSS packages (66 hours):

- computer statistical analysis and data processing using Excel and Gnumeric ;

- solving descriptive statistics problems using Excel and Gnumeric ;

- hypothesis testing in Excel, Gnumeric . Parametric and nonparametric methods;

- correlation and regression analysis in Excel, Gnumeric ;

- solving problems of variance analysis in Excel, Gnumeric ;

- methods of time series analysis in Excel, Gnumeric ;

- computer statistical analysis and data processing using SPSS;

- preliminary preparation of data in SPSS, description and entry of data into SPSS, recoding, grouping and calculation of new variables;

- one-dimensional frequency distributions and descriptive statistics;

- SPSS graphical capabilities;

- calculation of sampling error and confidence intervals in SPSS;

- testing statistical hypotheses in SPSS;

- analysis of statistical relationships using contingency tables;

- correlation and regression analysis in SPSS;

- dispersion, factor, cluster and discriminant analysis in SPSS.

Recommended primary literature, teaching and methodological kits, electronic resources

Klyachkin, V. N. Statistical methods of data analysis: textbook / V. N. Klyachkin, Yu. E. Kuvaiskova , V. A. Alekseeva. — Moscow: Finance and Statistics, 2021. - 240 p. - ISBN 978-5-00184-057-2.

Volchek, A. A. Mathematical methods of data processing in ecology: a textbook for students of higher education institutions majoring in "Environmental protection activities (by areas)" / A. A. Volchek [et al.]. - Minsk: RIVSh, 2018. - 210 p.

Maksimov, S.I. Technologies for processing research data in IBM SPSS Statistucs : a teaching aid / S.I.Maksimov , E.M.Zaytseva . - Minsk: RIVSh, 2016. - 100 p. - (series "Modern information technologies").

Teaching methods

Project-based, problem-based, dialog -heuristic

Language of instruction

Russian

Conditions (requirements), current control in the Far Eastern Federal District

Final assessment form

defense of the thesis