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An Introduction to JASP: A Free and User-Friendly Statistics Package James Bart

An Introduction to JASP: A Free and User-Friendly Statistics Package James Bartlett 1 Introduction 1.1 What is JASP? JASP is a free, open-source alternative to SPSS that allows you to perform both simple and complex analyses in a user-friendly package. The aim is to allow you to conduct complex Classical (stuﬀwith p values) and Bayesian analyses ("What the hell is Bayesian statistics?" you might ask, look in appendix 9.1 if you are interested), but have the advantage of a drag-and-drop interface that is intuitive to use. 1.2 Why JASP? Although many universities predominantly use SPSS, it is extremely expensive which means you probably cannot use it unless you are aﬃliated with a university. JASP is a free, open-source alternative that aims to give you a simple and user-friendly output, making it ideal for students who are still getting to grips with data-analysis in psychology. Here are just a few beneﬁts of using JASP: 1.2.1 Eﬀect sizes Eﬀect sizes are one of the most important values to report when analysing data. However, despite many papers and an APA task force (...in 1999, no one ever listens) explaining their importance, SPSS only oﬀers a limited number of eﬀect size options and many simple eﬀect sizes are required to be calculated manually. On the other hand, JASP allows you to simply tick a box to provide an eﬀect size for each test. 1.2.2 Continuously updated output Imagine you have gone through all of the menus in SPSS to realise you forgot to click one option that you wanted to be included in the output. You would have to go back through the menus and select that one option and rerun the whole analysis, printing it below the ﬁrst output. This looks incredibly messy and takes a lot of time. In JASP, all of the options and results are presented on the same screen. If you want another option to be presented, all you have to do is tick a box and the results are updated in seconds. 1.2.3 Minimalist design For each statistical test, SPSS provides every value you will ever need and more. This can be very confusing when you are getting to grips with statistics and you can easily report the wrong value. In JASP, the aim is minimalism. You start oﬀwith the bare bones result, and you have the option to select additional information if and when you need it. 1.3 Using JASP 1.3.1 How to download JASP Today, you will opening JASP through the software portal, but you can download it yourself for free on their website for either Windows, OSX, or Linux (if that’s your thing). Installing it should be pretty straightforward, just follow the instructions it provides you. After installing it and opening the program, you will ﬁnd the "Welcome to JASP" window shown in Figure 1. 1 Figure 1: JASP startup window 1.3.2 Entering data in JASP The ﬁrst diﬀerence you will ﬁnd between SPSS and JASP is how you enter data. In SPSS, you enter data manually through the data view screen. In JASP, there is currently no facility to enter data directly (although this may change in future), and you have to load the data in a comma separated values (.csv) ﬁle. This is like an Excel spreadsheet but you cannot directly load a normal Excel Workbook (.xlsx), you ﬁrst have to convert it to a .csv ﬁle. The data you will use today is already in a .csv ﬁle so you will be able to load it directly. However, if you decide to use JASP in your own time and need to create a .csv ﬁle, here is a useful link that explains what it is and how to create one. If you have an SPSS data ﬁle and want to convert it to .csv, look in appendix 9.2 for further instructions. To start any data analysis, we need to load some data to use. At the top of the "welcome" window, there are two tabs: File and Common. Click on the File tab and you will see the window in Figure 2. Here you will have your recently opened ﬁles on the right if you have used it before, but yours should be blank the ﬁrst time you use it. To open a ﬁle, click on Computer > Browse, then select the data ﬁle from wherever you saved it on your computer. After it has loaded, the "welcome" window will look slightly diﬀerent as your data will be visible on the left side of the window like in Figure 3. 1.3.3 Changing data types The next step is to make sure JASP knows what type of data your variables are (e.g. nominal, ordinal). Unlike SPSS, JASP does its best to guess what data type it is. The symbols at the top of the columns in Figure 3 look like three circles for nominal data, three lines like a podium for ordinal data, and a little ruler for scale data. Most of the time JASP gets it right and the columns have the right symbol. However, sometimes it is not quite right. If you click on the symbol, you can change it from one data type to another if things are not quite right. Another diﬀerence between JASP and SPSS is how you deﬁne nominal factor levels. In SPSS, you might remember that to deﬁne an independent groups factor such as nationality you need to assign each level a value and label. For example, you could list the ﬁrst participant as German and label them with a 1, the second person could be Chinese and be assigned a 2. Every German participant would be identiﬁed by the number 1, and every Chinese participant would be labeled 2 etc. However, in JASP you have the choice of using values as factor levels or using labels as factor 2 Figure 2: JASP ﬁle tab levels. You just need to make sure the variable type is nominal (three little circles) at the top of the column. An important thing to note is that if you use labels, all of them need to be exactly the same to be considered the same condition throughout the dataset. For example, German could not be spelled as german or GERMAN, or JASP would think these are three diﬀerent conditions. It has to be written exactly the same, capitals and spaces and everything. 2 Today’s session The session is organised like the process you would normally go through when you perform data analysis. You want to get a feel for the data through descriptive statistics and using some plots to visualise the data. The next step is to make sure the type of analysis you want to perform is appropriate for the data you have, so we will look at data screening. Finally, we will go ahead and look at the inferential statistics. There are tasks listed throughout the guide. Make sure you have the worksheet open to be able to write your answers down as you go along. The data for all of the examples are from real published research and were made available on the Open Stats Lab (McIntyre 2016). All the analyses you are going to perform are the same as what was performed in the original research. 3 Example One: T-test 3.1 Study background The ﬁrst example that we are going to look at is from a study by Schroeder and Epley (2015). The aim of the study was to investigate whether delivering a short speech to a potential employer would be more eﬀective at landing you a job than writing the speech down and the employer reading it themselves. Thirty-nine professional recruiters were randomly assigned to receive a job application speech as either a transcipt for them to read, or an audio recording of them reading the speech. The recruiters then rated the applicants on perceived intellect, their impression of the application, and whether they would recommend hiring the candidate. All ratings were on a likert scale ranging from 0 (low intellect, impression etc.) to 10 (high impression, recommendation etc.). 3 Figure 3: JASP window with data 3.1.1 Task 1. What would your predictions be? As they are the same words, do you think the applicants would be rated similarly, or do you think the audio recordings would result in higher ratings due to additional indicators of intelligence? It is important to think about this ﬁrst, so write your prediction down brieﬂy. 3.2 Descriptive statistics 3.2.1 Loading the data Firstly, we need to open the data ﬁle for this example. Look back at section 1.3 on how to open a .csv ﬁle and open Schroeder-Epley-data.csv from the folder you downloaded at the start of the session. Your window should now look like Figure 3. The next thing to do is to make sure JASP has correctly labeled each column. The variables we are interested in for the ﬁrst example are Condition, Intellect_Rating, Impression_Rating, and Hire_Rating. Condition is our independent variable and indicates whether the participant has uploads/Litterature/ jasp-guide.pdf