00:01
Now this probably wanted to develop realistic examples, the random variables, for which we'd have first, a positive covariance.
00:13
A positive total variance.
00:16
Now this would indicate that the variables move in the same direction.
00:21
So for our examples here, what about height and weight? just in general, the taller of a person is, the more that that person tends to weigh.
00:33
And so we would say that height and weight, positive covariance.
00:42
Now let's look at negative covariance.
00:50
Negative covariance would be the exact opposite.
00:53
This means when one goes up, the other one goes down, they're inversely related.
00:58
So what about the number of absences and a student's grade? as the absences go up, the grade is likely to go down.
01:17
As absences go down, the grade is likely to go up...