4.1 Data variables

First, it’s important to understand the different types of variables in jamovi and how they map onto our levels of measurement.

Variables in jamovi can be one of three data types:

  1. Integer, meaning the values are discrete whole numbers
  2. Decimal, meaning the values are numbers with decimals
  3. Text, meaning the values are alphanumeric, not just numeric

Furthermore, variables in jamovi can be one of four measure types:

  1. Nominal

  2. Ordinal

  3. Continuous (meaning jamovi combines interval and ratio and doesn’t distinguish between the two)

  4. ID (used for any identifying variable you likely wouldn’t ever analyze, like participant ID number or name)

There are a few great things about jamovi when it comes to these data variables. First, jamovi will try to automatically determine what the data and measure types are when you type in data or when you open a dataset; this is fabulous, until it goes wrong. It’s important that you always double check your data and measure types first!

Second, those little icons will be really helpful to let you know what variables can go in which boxes. For example, we would never analyze a nominal variable as our dependent variable for a t-test, and jamovi will help remind you of that. When performing an independent samples t-test, the dependent variables box will have a little ruler icon indicating you should be putting continuous variables in that box. Similarly, it will tell you to put nominal or ordinal variables in the grouping variable (independent variable) box. Sweet!