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, if you use a t-test the variable type will be coerced to continuous. However, if this is not possible (e.g., for text) you will not be able to conduct a t-test.
Variable Type Assignment
When loading a file with another variable type, JASP automatically assigns variable types according to the following rules:
- If the variable contains only integer values and missing values, it is assigned Continuous if there is only one unique value, Nominal for two unique values, Ordinal for three to ten unique values, and Continuous for more than ten unique values.
- 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. If you try to change a variable type and it has values that are not compatible, then JASP will not allow the conversion.
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.
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.