Before you do anything else, we strongly recommend that you visit the JASP YouTube channel and the ‘How to Use JASP’ page, where you can find introductory blog posts and videos. Below is some general information about JASP that may be helpful as you analyze your first data set. We invite you to post any remaining questions on the JASP forum or on the JASP GitHub page.
JASP comes with a series of example data sets that can be accessed from the ‘File → Open’ tab. Selecting an example data set will open it in JASP for inspection, editing, and analysis. In addition to its own .jasp format, JASP can open data sets in formats such as .csv (comma-separated values), .txt (plain text), .sav (IBM’s SPSS), and .ods (OpenDocument Spreadsheet). Note that all files need to have a header row that contains names for each of the columns or variables. Missing values can either just be missing (i.e., an empty cell) or be denoted by “Nan”, “.” (period), or ” ” (space). When opening a file, JASP makes a best guess to assign variable types, as explained below.
JASP distinguishes four variable types:
- Nominal Text
Nominal Text variables are categorical variables without numeric value (i.e., strings). An example might be a variable called “Favorite Dutch Soccer Club”, with three possible entries: “Ajax”, “PSV”, and “Feyenoord”.
Nominal variables are categorical variables that are represented by numeric values. For example, a variable “Group” may have levels “1” and “2”. Even though these are numbers, they do not imply an order, and the distance between them is not meaningful.
Ordinal variables are categorical variables with an inherent order. An example might be a Likert preference rating scale with levels 1 (“hate it”), 2 (“yuk”), 3 (“meh”), 4 (“cool“), and 5 (“in love”). Note that the distance between the numbers is not meaningful. JASP assumes that all ordinal variables have been assigned numeric values.
Continuous variables are variables with values that allow a meaningful comparison of distance. Examples include income, IQ, or weight.
Variable types in JASP are often enforced; for instance, you are not allowed to conduct a t-test when your dependent measure is nominal.
Variable Type Assignment
When loading a file, JASP automatically assigns variable types according to the following rules:
- If the variable contains only integer values and missing values, and contains fewer than 25 unique values, then it is assigned a variable type of Nominal.
- If the variable contains only integer values, floating point numbers, missing values, and +/- infinities, then it is assigned a type of Continuous.
- Otherwise the variable is assigned a type of Nominal Text.
Changing Variable Types
If need be, the automatic variable type assignment can be corrected manually. When you click the icon representing the variable type at the top of the column, a menu is produced that allows you to choose a different variable type. Values incompatible with the new variable type are automatically converted to missing values. But be careful! JASP presently does not feature an “undo” facility, so if you change a Nominal Text column full of text values to a type such as Continuous, the entire column will be converted to missing values. At present, there is no way to undo this action and it will be necessary to reload the data set.
Having loaded a data set, it is now possible to run analyses. After selecting an analysis from the ribbon along the top you will see input options for that analysis in the left panel, and the associated output in the right panel. As the input options are specified, the analysis results automatically update, providing immediate feedback.
When the analysis has been specified to your satisfaction, you can return to the data view by clicking the “OK” button. You can return to an earlier analysis simply by clicking on the output of interest. This brings up the options that were used to generate that analysis, and allows you to make adjustments or additions.
There is much more to say about JASP: its ability to annotate output, to interact with the Open Science Framework, to conduct sophisticated analyses using modules, to save APA tables and publication-ready figures, and much more. These options are discussed in our YouTube videos. We are also in the process of writing a JASP manual.