00:01
So we have some questions about correlation.
00:06
So we have question four, which says that we're given the correlation between weight and pounds and height and feet.
00:15
So are 0 .58.
00:18
And we want to find the correlation between weight and pounds and height and yards and the correlation between weight and kilograms and height and meters.
00:26
So it's going to be the same.
00:28
The correlation is the same for all three because when you find the these units don't matter essentially because you state what it does the calculation for r standardizes the standardizes the score so it's and you're measuring the same thing we humans put units we put you know we put my pounds and feet on some some things that we used to measure the weight of someone and the height of someone.
01:13
But it doesn't matter.
01:14
They could be pounds and yards.
01:20
They could be pounds, was it, kilograms and meters.
01:25
It doesn't matter.
01:26
Regardless, the person is still the same height, and they're, whatever they're weighing, how much mass they're taking up is the same.
01:37
So it doesn't affect anything.
01:40
All right, that's enough there.
01:40
Five, or should say six, actually.
01:46
For a certain class, the relationship between the amount of time spent studying and test grader ended was examined, it was determined that the amount of time they studied increased, so did their grades.
01:57
It's positive.
01:58
That's a positive relationship.
02:00
Because if you're looking at a graph, as time went up, there's time, grades went up as well.
02:08
So it's going like that.
02:10
So it's a positive correlation.
02:16
Seven.
02:18
And for the same class, the relationship between the amount of time spent studying and the amount of time spent socializing was also examined.
02:27
That's interesting.
02:28
It was determined that the more hours they spent studying, the few hours they spent socializing.
02:33
Well, this is negative because, again, look at that graph, as the time spent studying, the socializing time decreased.
02:47
But as time went on, socializing went down.
02:52
So that's how we view that.
02:55
So it's negative.
02:58
And these up arrows here on the y -axis, that just means bigger values are on top.
03:04
Bigger values go up.
03:07
Right.
03:08
And then we have number 10.
03:11
True false, the correlation in real life height, or in real life between height and weightness r equals 1.
03:18
R equals 1 is a perfect correlation.
03:21
Like you might as well make it an equation.
03:23
And y equals 3x plus 1.
03:27
But that's not the case because there's always a little bit of error.
03:30
So this is false.
03:35
Which says 12.
03:37
Two variables with the correlation of 0 .3 have stronger linear relations of the two variables with correlation of negative 0 .7.
03:45
That's false because r measures the strength of a relationship and it can go between 1 and negative 1.
03:53
And the closer you are to negative 1, and the closer you are to one, you're really strong.
03:59
Whereas the closer to zero, the less strong it is.
04:02
So negative 7, negative 0 .7, while less than 0 .3, is still closer to negative 1.
04:15
And so a lot of times what we do in terms of strength, we look at this, the absolute value of our...