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jamoviguiden is available in English or Swedish. It contains brief, accessible guides (with pictures) of commonly used procedures in jamovi. To keep the content short, no (or little) description of the assumptions behind the statistical tests and how to interpret the results is described. When you get started, it's often easy to explore on your own.
To learn more about jamovi and statistics, the (free!) e-book ”Learning statistics with jamovi” by Danielle Navarro and David Foxcroft is recommended.
Barton Poulson created a great series of introductory videos covering (more or less) all analyses that can be done with jamovi.

jamoviguiden was created by Jonas Rafi and is available in English or Swedish. It is licensed under Creative Commons License Attribution-Non Commercial 4.0 International License CC-BY-NC 4.0.

Tips and tricks for using jamovi

Cleaning your data and checking assumptions for your main analyses

A quite essential part of a statistical analysis actually happens before we conduct them. That part is concerned with cleaning you data in order to fulfil the assumptions required to run most inference-statistical procedures. At the core of "cleaning you data" is the search for and the removal of outliers. Using filters can help you with that task.
One of the aims when cleaning outliers is that they might lead to violations of assumptions for parametric statistical tests: normality (and possibly linearity; due to floor and ceiling effects). I will briefly introduce how we can conduct two preliminary checks to assess whether the assumptions for conducting our main analyses are met: The first is to check whether the data are in accordance with a normal distribution, the other one is to assess whether the independent and the dependent variables stand in a linear relation.

From SPSS to jamovi

Quite a few of us are so used to SPSS that we are a little scared to switch to another software because such transition and to get acquainted with a new software always takes time and effort. Now might be a good time to switch because SPSS is also introducing a new interface with version 26 which at least requires getting used to something new and learn it. Why not take a little bigger step and learn jamovi? jamovi does not entail the incredibly high license costs of SPSS (from $ 1290 / year for Base Package) and can be a first step on the road to R. jamovi tries to use an interface that is relatively similar to the one in SPSS, the result version is more transparent and can be easily transferred to text processing (copy-and-paste with [mostly] keep formatting).

Comparison of analyses: provides an overview of which analysis functions are available in SPSS and the respective functions in jamovi.

Side-by-side: Shows a side-by-side comparison of how something is done in SPSS and in jamovi.

From jamovi to R

There are two possible ways of using R code together with Jamovi. The first one is based upon the use of the jamovi-module Rj. The other, more powerful one is based upon creating analyses within the jamovi user interface, copying the syntax and using it inside R in connection with the R-library jmv.
Especially the latter option with direct access to R gives you access the functionality of its built-in functions as well as to masses of R-libraries dealing with (more or less) every statistical problem you can imagine.

To learn more about R you can use two excellent websites by Danielle Navarro. The first is "Learning statistics with R" and has psychology students who use R in their first method course as the main target group. On this page you will find a PDF and a bookdown version that was the basis for «Learning statistics with jamovi» (mentioned above). The second resource "R for Psychological Science" is still under construction and aimed more at someone who has taken at least one research method class and would like to learn to use the R programming language in their own work. This site also has a strong focus on the tidyverse methodology of Hadley Wickham.

The SPSS-to-jamovi and jamovi-to-R sections were created by Sebastian Jentschke and are licensed under [http: //creativecommons.org/licenses/by-nc/4.0 Creative Commons Attribution-Non Commercial 4.0 International License] link = http: // creativecommons.org/licenses/by-nc/4.0.