 Continuing an R in introduction, the next thing we need to talk about is basic statistics and we'll begin by discussing the basic summary function in R. The idea here is that once you have done the pictures that you've done the basic visualizations, then you're going to want to get some precision by getting numerical or statistical information. Depending on the kinds of variables you have, you're going to want different things. So for instance, you're going to want counts or frequencies for categories. And they're going to want things like core tiles and the mean for quantitative variables. We can try this in R and you'll see that it's a very, very simple thing to do. Just open up the script and follow along. What we're going to do is load the datasets package, controller command and then enter. And we're actually going to look at some data and do an analysis that we've seen several times already. We're going to load the iris data. And let's take a look at the first few lines. And again, this is for quantitative measurements on the sepulon petal length and width of three species of iris flowers. And what we're going to do is we're going to get summary in three different ways. First, we're going to do summary for a categorical variable. And the way we do this is we use the summary function. And then we say iris because that's the data set and then a dollar sign and then the name of the variable that we want. So in this case, it's species, we'll run that command. And you can see it just says Satosa 50, VersaColor 50 and Virginia 50. And those are the frequencies or the counts for each of those three categories in the species variable. Now we're going to get something more elaborate for the quantitative variable. We'll use sepulon for that one. And I'll just run that next line. And now you can see it lays it out horizontally, we have the minimum value of 4.3, then we have the first quartile of 5.1, the median, then the mean, then the third quartile, and then the maximum score of 7.9. And so this is a really nice way of getting a quick impression of the spread of scores. And also by comparing the median and the mean, sometimes you can tell whether it's symmetrical or there's skewness going on. And then you have one more option and that is getting a summary for the entire data frame or data set at once. And what I do is I simply do summary. And then in the parentheses for the argument, I just give the name of the data set iris. And this one I need to zoom in a little bit. Because now it arranges it vertically, where we do sepal length. So that's our first variable. And we get the quartiles and we get the median, then we do sepal width, pedal length, pedal width, and then it switches over at the last one species where it gives us the counts or frequencies of each of those three categories. And so that's the most basic version of what you're able to do with the default summary variable in R gives you quick descriptive gives you the precision to follow up on some of the graphics that we did previously. And it gets you ready for your further analysis.