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Tutorial: JASP for beginners

Authors: Heo, Ihnwhi; Veen, Duco; Van de Schoot, Rens;

Tutorial: JASP for beginners

Abstract

{"references": ["JASP Team (2020). JASP (Version 0.12.2)[Computer software].", "Van de Schoot, R., & Depaoli, S. (2014). Bayesian analyses: Where to start and what to report. The European Health Psychologist, 16(2), 75-84.", "Van de Schoot, R., Kaplan, D., Denissen, J., Asendorpf, J. B., Neyer, F. J., & Van Aken, M. A. (2014). A gentle introduction to Bayesian analysis: Applications to developmental research. Child development, 85(3), 842-860. https://doi.org/10.1111/cdev.12169", "Van de Schoot, R., van der Velden, F., Boom, J., & Brugman, D. (2010). Can at-risk young adolescents be popular and anti-social? Sociometric status groups, anti-social behaviour, gender and ethnic background. Journal of adolescence, 33(5), 583-592. https://doi.org/10.1016/j.adolescence.2009.12.004"]}

This tutorial introduces the fundamentals of JASP (JASP Team, 2020) for starters. Our explanation starts with the installation of JASP, the screen structure of JASP, and loading data. Given the data loaded, we explore data via descriptive statistics and data visualization. We further explain how to perform correlation analysis, multiple linear regression, t-test, and one-way analysis of variance from a frequentist perspective and draw conclusions from outputs.

Since we continuously improve the tutorials, let us know via Github (https://github.com/Rensvandeschoot/Tutorials) if you discover mistakes, or if you have additional resources we can refer to.

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Keywords

tutorial, statistics, biomedical science, social science, data analysis, JASP, methodology, behavioral science, psychology

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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