Dataset individuals and categorical variables

So we have this question that says millions of Americans rely on caffeine to get them up in the morning, and that is probably true. Although for me, if I drink even a little bit of caffeine in the morning, I won't be able to sleep that night. Here's nutritional data on some popular drinks at Ben's Beans Coffee Shop.

We have the names of different drinks, and for each of those drinks, we know not only their name, we know whether they are hot or cold, we know how many calories they contain, sugar content, caffeine. All right, now with that, let's try to answer these questions. Like always, try to pause the video and see if you can answer these questions before I do.

And on this one on the right, there's a little bit below where you see; there's a little bit below, and actually, I'll just leave it there. So the individuals in this data set are... So when you see the term individuals, you might immediately say, "Oh, they must be talking about people," because in everyday language, when we talk about individuals, we tend to be talking about people. But in statistical language, it's really referring to what are the different entries of the data set.

So each of these rows of the data set, they're not referring to types of people or customers and things about those customers. So it's not about Ben's Beans customers. I have trouble saying that. Each of these rows represents one of the drinks that are offered at Ben's Beans Coffee Shop. So those are the individuals in statistical language.

The individuals could refer to things—what are the things representing Ed in that data set? Then we're asked what the data set contains, and we're asked how many variables it contains and whether or not they're categorical or not.

So first, what's a variable? Well, the variables are what are the things that are different about these different entries, about these different individuals that this table tells us about, that this data set tells us about. Well, the name is a variable; each of these drinks has different names—that's one variable. The type is a variable; they can be hot or cold. The calories are a variable, the sugar content is a variable, and the caffeine is a variable.

So we have five variables over here: the name, type, calories, sugar, caffeine. So we have five variables, so we can rule out the six variable choices right over there. We're going to rule that one and that one out.

And so how many of these are categorical? A categorical variable—let me write this down—categorical variable means that you're going to that dimension of the thing you're measuring is going to be placed into some categories, or that variable takes on values that are the name of a category.

So for example, drink name—this is a categorical variable because the values that drink name can take on, well, those are the actual names of the drinks. These are the categories. It could be brewed coffee, café latte, café mocha, cappuccino, so on and so forth.

So this one right over here is... is this one over here categorical. Now, you might say, "Well, what's another type of variable?" Well, another type of variable is quantitative. A quantitative variable is going to take on numerical values as opposed to categorical values, numerical values that are measuring some type of attribute.

So, let's go through these. So what about type? Well, type isn't a numerical value; it's taking on a category. It's either going to be hot or cold, so that is also going to be categorical. But these other three, these take on numerical values that represent, in the case of calories, the number of calories a serving has, the amount of sugar in the sugar variable, or the amount of caffeine in the caffeine variable.

So these three right over here, these are quantitative variables. So you have five total variables, two of which are categorical and three of which are quantitative. And so that is this choice right here: five variables, two of which are categorical. The two categorical ones are, well, what name, what's the name of the drink, and also whether they are hot or cold.