 is pretty, again, it doesn't show a high correlation, right? The dots are not highly correlated. Now, when my hypothesis would have been that as they get older, maybe their batting average would go down. That's why I put the age over here on the X as the independent factor, which would be driving the batting average, right? But if I flip these two around, I can say, I can say, well, what if I put the age over here on the Y, you still get that negative correlation, but now it's just flipped the other way around. So it's just a matter of thinking of trying to get an idea of which you think is the causal factor. And usually we try to put the independent factor or the thing that's causing the other factor on the X, but that could just be a hypothesis here. There doesn't seem to be a significant causal factor between just these data. Now, we can also go to our data analysis and allow it to give us our descriptive statistics just to show that in Excel. So we're gonna give the statistics for the summary data and the confidence level. And that spits out this, which gives us a nice summary, it gives us our mean, our standard error, the median, the mode, the standard deviation, the ketosis, sample, various units, range, minimum, maximum sum and count. Now, these are not dynamic. They don't move as we change the data or anything like that, but they're a great tool to first start putting something together, a model together, and then you might do these with an actual formula just to double check or to kind of double check your numbers. But this kind of analysis of the two data sets, age and the batting average, might give us some insights sometimes, which might give us more hypotheses and whatnot to see what we wanna do going forward in terms of thinking about correlations and how these data sets might be related. Now, if that didn't work, we can say, okay, let's pick some other data. So we can go back to our data sets and say, well, let's try the batting average and the RBI. Now, the batting average is how many times they get on base and the RBI's are the runs that were batted in. So meaning the hit that they got drove a run in which actually scored a run or a point, right, a run. So that means, so if that's the case then, then I would think my hypothesis would then be that a higher batting average would be kind of the causal factor and I would think that their RBI's would go up, right, because if they got more hits, you would think the RBI's would go up. Now, this one's a little bit careful, a little bit weird, however, because you'll note that the batting average is in terms of a percent, a ratio, meaning how many times did they get on base versus how many times did they have the opportunity to get on base here represented with a decimal, but could be represented with a percent, whereas the RBI is just an absolute number, meaning how many RBI's do they have. So you gotta keep that in the back of the mind and say, well, that's a little bit kind of weird, because obviously if someone had more at bats, even if their batting average was lower, they got on base less percentage of the time, they might have more RBI's, because they had more opportunities to hit someone in, right? So you might think that maybe the RBI's, we should do the RBI's as a percentage of at bats or something like that, where we're comparing percents to percents. So just something to kind of keep in mind, but we'll keep these data and see what happens with it. So notice the RBI's, if I plot this, I get an interesting histogram. So now I'm just plotting the RBI's and most of them are the zero to 9.8 and then tapering down from that point. And so, and then we have the batting averages, which we saw before, which are going to be, as we would think, more kind of bell shaped because this is the average of kind of performance in terms of getting on base. Now again, if we went to the RBI's up top and we took the RBI's like as a percentage of at bats and we did the same kind of thing and that we did with the batting average, trimming off the really high numbers and the low numbers, we might in that case get something that's more bell but we'll continue with this. Let's do our calculation over here. So here's our mean of the batting average and the RBI's meaning the average of these two numbers.