Jamovi: An Easy to Use Statistical Software for the Social Scientists

This report aims to introduce the fundamental features of the free Jamovi software to academics in the field of educational measurement for use at undergraduate and graduate level research. As such, after introducing the R based interface and the integrated development environment, the core functions of Jamovi are presented, the installation for GNU7Linux, Windows, and MacOS is explained and screenshots of frequently conducted statistical analyses are provided. Additionally, the module support of Jamovi is presented, along with a use case scenario on developing further functionality for Jamovi using modules. Specifically, conducting meta-analysis and Bayesian statistics using modules in Jamovi are explained through examples.

Anahtar Kelimeler:

Jamovi, R, Statistical software, Free software

Jamovi: An Easy to Use Statistical Software for the Social Scientists

Keywords:

Jamovi, R, Statistical software, Free software,

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Amazon (2019). Search Results. https://www.amazon.com/s?k=statistics+for+social+science Accessed on 20 September 2019.
Baykul, Y. (2000). Eğitimde ve psikolojide ölçme [Measurement and Evaluation in Education]. Ankara: ÖSYM Yayınları.
Brown, T.A. (2015). Confirmatory factor analysis for applied research. New York: The Guilford Press.
Field, A. (2013). Discovering statistics using IBM SPSS statistics. London: SAGE Pub.
Fokkema, M. & Grieff, S. (2017). How performing PCA and CFA on the same data equals trouble. European Journal of Psychological Assessment, 33(6), 399–402.
GNU (2019). What is GNU? https://www.gnu.org/ Accessed on 28 September 2019.
Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179-85.
Henson, H. K. & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological Measurement, 66(3). 393-416.
JASP Team (2019). JASP (Version 0.11.1) [Computer software].
Kline, R. B. (2009). Becoming a behavioral science researcher: A guide to producing research that matters. New York: Guilford Press.
Muenchen, R.A. (2019). The Popularity of Data Science Software. http://r4stats.com/articles/popularity/. Accessed on 20 September 2019.
Navarro, D.J. & Foxcroft, D.R. (2019). Learning statistics with jamovi: A tutorial for psychology students and other beginners. (Version 0.70). doi: 10.24384/hgc3-7p15 [Available from http://learnstatswithjamovi.com]
Padilla, M. A & Divers, J. (2016). A Comparison of composite reliability estimators: Coefficient omega confidence intervals in the current literature. Educational and Psychological Measurement, 76(3) 436–453
R Core Team (2019a). What is R. https://www.r-project.org/about.html Accessed on 25 September 2019.
R Core Team (2019b). Contributed Packages. https://cloud.r-project.org/web/packages Accessed on 01 October 2019.
RKWard (2019). About RKWard. https://rkward.kde.org/About.html Accessed on 05 October 2019.
RStudio (2019). RStudio. https://rstudio.com/products/rstudio/ Accessed on 05 October 2019.
The jamovi project (2019a). Jamovi (Version 1.0) [Computer Software].
The jamovi project (2019b). About. https://www.jamovi.org/about.html Accessed on 06 October 2019.
Warner, R.M. (2008). Applied statistics: From bivariate through multivariate techniques. USA: SAGE Pub.