Author(s):
- Ostapenko Yana Oleksandrivna, ORCID: https://orcid.org/0000-0002-9386-2237
DOI: https://doi.org/10.30929/2307-9770.2021.09.01.09
Paper Language: UKR
Abstract
The use of computer technology in the educational process allows you to quickly and efficiently process large amounts of information obtained as a result of research and determine the impact of certain factors on the phenomenon or process under study. It is important for a psychologist to be able to properly analyze and process the data he receives as a result of psychological research. The use of statistical methods of data processing is an integral part of the analysis of psychological processes. The specificity of statistical processing of the results of psychological observations is that the database being analyzed is characterized by a large number of indicators of different types, their high variability under the influence of uncontrolled random phenomena, the complexity of correlations between variable samples. In this regard, one of the necessary conditions for the formation of research competence of a psychologist is to master the methods and criteria of statistical analysis. The article highlights the importance of mastering the statistical analysis of psychological phenomena and processes using computer technology for future psychologists. The essence of the main methods of statistical analysis is revealed: descriptive statistics, correlation analysis, methods of regression analysis, indicators of dynamics and detection of development trends, as well as forecasting the development of a psychological phenomenon or process in the future. The application of statistical methods using spreadsheets of Місrоsоft Ехсеl is demonstrated, as the simplest and free, and therefore available to the average higher education-future psychologist and analysis of the results of processing indicators. Performing tasks of an applied nature with the use of computer technology helps to facilitate the perception of the material and a deeper mastery of the discipline "Statistical analysis and modeling of psychological processes" and the essence of the psychological processes themselves. Allows you to gain the skills of statistical analysis to find optimal solutions. The efficiency of using Microsoft Excel for statistical analysis of psychological phenomena is proved. The proposed methodological approach is implemented in the educational process. As a result of observation of classes the received results are generalized and systematized. Further research is proposed to model the phenomena and processes in psychology.
Keywords
statistics; statistical analysis; computer technology in psychology; Microsoft Excel
References
- Glass, J., Stanley, J. (1976). Statistical methods in pedagogy and psychology.[Statisticheskie metody v pedagogike i psikhologii]. M., 495 р. [in Russian]
- Hryshyna, A. V. (2015). Mathematical methods in psychology [Matematychni metody v psykholohiyi]. Kyiv, Ukraina: Instytut kryminalno-vykonavchoi sluzhby, [in Ukrainian].
- Klymchuk, V. O. (2008). Teaching the course "Mathematical methods in psychology in terms of credit-module system"[“Vykladannya kursu “Matematychni metody u psykholohiyi” v umovakh kredytno-modul'noyi systemy”], Sotsialna psykholohiia[,Sotsial'na psykholohiya], 2 (28), 180-189. [in Ukrainian].
- Klymchuk, V. O. (2009). Mathematical methods in psychology [Matematychni metody u psykholohiyi]. Kyiv, Ukraina: Osvita Ukrainy. [in Ukrainian].
- Litnarovych, R. M. (2006). Fundamentals of mathematical statistics in psychology[Osnovy matematychnoyi statystyky u psykholohiyi]. Rivne, Ukraina: MEHU. [in Ukrainian].
- Olefir, V. O. (2016). Mathematical methods in psychology: guidelines for organizing and planning independent work of students. for applicants for educational qualification level bachelor's degree in specialty 053 – psychology [Matematychni metody v psykholohiyi: metodychni vkazivky z orhanizatsiyi ta planuvannya samostiynoyi roboty stud dlya zdobuvachiv osvitn'o-kvalifikatsiynoho rivnya bakalavr za spetsial'nistyu 053 – psykholohiya.]. Kharkiv, Ukraina: Kharkivskyi natsionalnyi universytet imeni V. N. Karazina.[in Ukrainian]
- Rudenko, V. M., Rudenko, N. M. (2017). Mathematical methods in psychology: a textbook [Matematychni metody v psykholohiyi : pidruchnyk]. Kyiv: Akademvydav, 384 p.
- Coombs, C. H., Dawes, R. M., Tversky, A. (1970). Mathematical psychology: An elementary introduction, Englewood Cliffs: Prentice-Hall, 419 p.
- Howitt, D., Cramer, D. (2010). Introduction to Statistics in Psychology. N.-Y.: FT
- Thorndike, R. L., Hagen, E. (1961). Measurement and evaluation in psychology and education. N. Y.: L.: Wiley, 597 p.
- Aivazian, S. A., Stepanov, V. S. (2021). Statistical data analysis software: benchmarking methodology and sample market overview[Programmnoe obespechenie po statisticheskomu analizu dannykh: metodologiya sravnitelnogo analiza i vyborochnyy obzor rynka]. URL: http://pubhealth.spb.ru/SAS/STatProg.htm. (accessed: 18.02.21). [in Russian]
- Vasylenko, Zh. V. Programmnoe obespechenie po statisticheskomu analizu dannykh. Metodologiya sravnitelnogo analiza]. Statistical data analysis software: benchmarking methodology and sample market overview. URL: //www.giac.unibel.by/sm_full.aspx?guid =8313 (accessed 20.02.21) [in Russian]
- Maiboroda, R. Ie., Sugakova, O. V. (2021). Statistical analysis of data using the STATISTICA package [Ctatystychnyy analiz danykh za dopomohoyu paketu STATISTICA]. URL: http://matphys.rpd.univ.kiev.ua/downloads/courses/mmatstat/StatAn.doc. (accessed 15.02.21) [in Ukrainian]
- Ostapenko, Ya. O. (2018). Use of PSPP during statistical analysis[Vykorystannya PSPP pid chas statystychnoho analizu]. Skhidna Yevropa: ekonomika, biznes ta upravlinnia, №2 (13). URL: http://www.easterneurope-ebm.in.ua/index.php/13-2018-ukr (accessed 15.02.21). [in Ukrainian]
- Ostapenko, Ya. O. (2017). Software products of statistical and economic-mathematical research in economic [Prohramni produkty statystychnykh ta ekonomiko-matematychnykh doslidzhen' v ekonomitsi]. International Scientific Conference Anti-Crisis Management: State, Region, Enterprise: Conference Proceedings, . Le Mans, France: Baltija Publishing, Part III, P.48-50, 17th, November, [in Ukrainian]
- Roik, M. V., Prysyazhnyuk, O. I., Denisyuk, V. O. (2017). Review of software for statistical data analysis [Ohlyad prohramnykh zasobiv statystychnoho analizu danykh], Effective Economics [Efektyvna ekonomika], № 7. URL: http://www.m.nayka.com.ua/?op=1&j=efektyvna-ekonomika&s=ua&z=5676 (accessed 15.02.21). [in Ukrainian]
- Andy Field. Discovering Statistics using SPSS. URL: https://www.discoveringstatistics.com/books/dsus/ (дата звернення 15.02.21).
- Bentler, P. M. (2006). EQS 6 Structural Equations Program Manual. Encino, CA: Multivariate Software, Inc., 418 p.
- Harrington, D.(2009). Confirmatory factof analysis. ‒ New York : Oxford University Press, Inc., 122 p.
- Ritz, Christian, Streibig, Jens Carl.(2008) Nonlinear Regression with R Springer-Verlag, New York, NY ISBN 978-0-387-09615-5. 144 pp.
- Spector, Phil (2008). Data Manipulation with R. Springer.157 p.
