00:01
So you basically have some data, 51 pieces of data, and you have the x weight as the beginning weight, and then this is the after weight.
00:13
And your sample size is 51, which really doesn't come into play in this.
00:18
And they said they got a correlation of basically 0 .7.
00:21
And so let's just say what this is explaining to begin with.
00:24
That says that as you look at the poundage, how much someone weighs at the beginning.
00:32
So at the beginning weight and versus the after weight, that you have a consistency as you look at the beginning weight increases as to does the after weight.
00:45
So it could be that there isn't any weight loss whatsoever.
00:47
It's just that there's consistency in the weight from the beginning to the after.
00:52
So if it was a perfect correlation, it could be that they weigh exactly the same weight, or they could have all gained 10 pounds.
00:59
So it's just giving me as the beginning weight increases you anticipate, the after weight will also increase.
01:06
So it doesn't show anything about weight loss.
01:09
So what should be done is the following.
01:12
We should be looking at the difference between the beginning weight minus the after weight.
01:20
And we would be assuming, and that would be called a difference, and we would be assuming that the mean of that difference is equal to zero, and alternately that that mean weight, we want the before weight to be higher than the after, we surely don't want them to have gained weight, so we would want that before minus after to end up being greater than zero, and that would show that there's a significant weight loss...