0:00
All right.
00:01
So in this question, we're told a student took two measurements, found this denier deviation of it, and thought their experiment was precise because it had a small standard deviation.
00:12
And we either have to confirm or deny that students ' assumptions about their experiment.
00:17
And so we have four possible answers.
00:21
And the first one is, is there standard deviation correct? it is because it has a small deviation, which means high precision.
00:30
This one, this is incorrect.
00:36
So a small standard deviation in general, in general, true.
00:48
But let's look at the definition of, or the mathematical formula for standard deviation, which is here with a sigma, i think, yeah, sigma.
01:00
It's the sum of the value you're finding the standard deviation for minus the mean of your status set squared n over one, which is the number of samples you ran, and then square rate the whole thing.
01:17
So if we're looking at this, if we only did two samples where n is equal to two, well, it's not very useful of this division here.
01:32
So usually you get smaller standard deviation with more samples.
01:36
And so usually when you only have two samples, your standard deviation is pretty high.
01:40
So this student gas model standard deviation simply out of luck.
01:45
So if we're throwing at our dartboard here, and we happen to get two right next to each other, well that's just pure luck.
02:00
Because if you throw a third, it could very well end up over here.
02:02
And then our standard deviation just skyrockets.
02:07
So that's why kind of matters how many samples you do.
02:11
Because if you start getting four or five or six right in a row, well, the near precision is really good.
02:17
So really, the number of samples you have starts to matter is just one, just two samples.
02:23
That could just be pure luck...