00:01
Okay, so the question says, an investigator measuring various characteristics of a large group of athletes found that the correlation between the weight of an athlete and the amount of weight that athlete could lift was 0 .6.
00:14
And then they say true or false and explain.
00:17
So part a says, on average, an athlete can lift 60 % of his body weight.
00:23
The r value being 0 .6 does not mean the athlete can lift 60 % of his body weight necessarily.
00:31
That's an inaccurate interpretation of the r value.
00:35
So for a, we're going to say false.
00:40
And again, it's just because the 0 .6 correlation value, correlation coefficient doesn't mean that the athlete can lift 60 % of his body weight.
00:52
It just means that the correlation between how much you can lift, how much the athlete can lift and the weight of the athlete is about 0 .6 in terms of strength.
01:06
In terms of linear strength.
01:10
For part b, it says, if an athlete gains 10 pounds, he can expect to gain an additional six pounds.
01:16
Sorry, he can expect to lift an additional six pounds.
01:19
That is also an inaccurate interpretation of the r value being 0 .6.
01:25
I think for this, they might have, this statement might be confusing r value with slope.
01:32
If the slope was like 0 .6, then maybe that would be true.
01:36
Depending on what you set your variables to.
01:39
But yeah, so that's also going to be false because in this case they misinterpreted what the r value means as well...