Variable types and labels - jamovi Tutorial

- Your computer can analyze data without knowing what it is, if it has numbers, it will work with numbers, if it has text, it'll do something. But, for it to mean something to you as the analyst, and maybe as your client, you have to know what things mean. And that means you need to define your variables, give them their variable types, as well as put labels on them, that are going to help you as you try to make sense of things. So, for instance, here's a small data-set. It's based on the one that I imported earlier. It begins with an ID number, That's helpful because you can go back and find particular cases, so you always want to start with that. Then I have three questions; Q1, Q2, Q3; that are on one to five, rating scales, and then I have a question here, I've called it Subscribed at the end, and it's Yes and No, or Y and N. Now, what we need to do is, say what kind of types each of these variables are, as well as give them labels as necessary. Now, ID, we don't really need to worry about this one, but by default, if Jamovi sees one through however many numbers, it's going to assume that it is a Continuous scale. Now, we want to change the type. You can do that either by double-clicking on the name of the variable here, or by going up to Data and then clicking Setup, either one will work. And so, the very first one is ID. Now, technically, ID numbers are not Continuous or Quantitative, they're Nominal, where it's one per person. So, I'm going to put Nominal, but I'm going to say Integer, that's fine, and we'll leave it like that. And you see now that it's little icon here has switched from the ruler to the three circles, which indicate different categories or buckets. That change by the way of, ID from Continuous to Nominal, it doesn't really make a difference. I'm going to go to the next variable, which is Q1, and this is where I actually want to give it a real name, and I might say something, Like Website, so, Do they like your website? And now that shows up here, now this isn't the label, I just changed the name of the variable. I could give it a more thorough description, Does the user like the company's website? Now, that label there is just for our own use, it doesn't really show up anywhere. But, what I'm going to do here is, I'm going to change the variable type, and I'm going the change the names of the levels. Now, it turns out that when you have a small number of categories that are 12345 as a small number, Jamovi assumes that it's a Categorical or Nominal variable. The thing is, it doesn't really make a difference if you're going to be averaging, or if you're going to be calculating statistics. It'll do it on these variables, even though they are defined as Nominal. You can change it to Continuous or Ordinal, and that's going to affect the kinds of graphs that you can make and is going to affect the ways that you can split the data, so it's not critical if all you're going to do is average, but if you want to do other things with it, it helps to define them. Now, a one to five rating scale, there's a debate about what level of measurement it is. Technically, it's Ordinal, because higher numbers indicate more agreement or a higher evaluation of something. On the other hand, in every field I've ever seen, people actually take a one to five rating scale and treat it as though it were Continuous or Quantitative, so they can average it. And so, I'm actually going to come here, and I'm going to define this one as Continuous. Now, you'll see here that the levels went away, because now it's treating these as time, one seconds to five seconds, doesn't have labels. So, that's fine and I know what it means, So, I'm going to go ahead to the next one, and I'm going to put here, Like Price of your service. And this one I'll put it as Ordinal. Now, you see that the levels here stayed, And that's important. The last one here I'll just put, Like Product. I'm going to leave this one as Nominal, but now I'm going to change these levels. I'm actually going to change these labels, so for instance, I click right here at one, and that's usually, Strongly Disagree, and then the two is, Disagree, the three might be, Neither, four would be, Agree, and five might be, Strongly Agree. A lot of people call this the Likert Scale, it's actually a Response Scale, Likert Scale's have more to do with, how you choose the questions, as a pose to the format in which you respond to them. But, call it Likert Scale if you want. It's a one to five Rating Scale. Now, you can see that these labels all show up down here, that's really the convenient thing. Remember, the numbers are still underneath there, so you can still do numerical operations on these variables. The last one I want to show you is, this text variable, at the end. You see it says Nominal text, because I actually typed in the letters, Y and N. You can do the same thing with these, I can click on the Y and I can put, Subscribed. I can maybe put they are not subscribed but they came from your website, so we'll call them a Visitor. So, now you have new names for the variables, I changed the names. I changed the levels of the measurement, or the type of the variable for some of them. Say or instance from, Continuous, or Quantitative to Ordinal, to Nominal or Categorical, and then they change labels, and so this is a very important step in terms of preparing the data into 'Movi. Because, it's going to make it mush easier for you to interpret the analysis. Then in turn to make sense of it, especially when you're collaborating with a colleague or potentially working for a client.