00:01
So jennifer, what i've done is i've taken all the x values and put them into list 1.
00:06
And then my list 2, i found the one variable statistics on list 1 and found that the x bar for that list is a 4 .42 and then the standard deviation is 1 .685.
00:27
And then i went up here into list 2 and put in the formula of list 1 minus the x bar divided by that sample standard deviation of x.
00:44
And these are my values.
00:45
And let me see what you need to have them rounded off to.
00:48
I think it's a two -place decimal.
00:49
It looks like a two -place decimal.
00:51
So you want all those z scores.
00:53
And so the z scores for this distribution, hopefully i can fit them in here.
00:56
I'll try to put them in kind of small, is .107, 1 .53.
01:06
I'll give you two decimal places after this.
01:09
.70, a negative .25, next one negative .37, next one is .46, next one is negative 2 .03, next one is negative 1 .08, next one .34, next one .58, and that's the last one.
01:39
So those are our values.
01:40
And then i also put into list 3 into, i'll get the color to change, well, third time might be a charm, into list 3, i did put my y values and then i could verify in list 4 that if i find the list 3 minus the y bar divided by the standard deviation of y that i could get those z scores.
02:06
So those are the first part of the problem.
02:09
Now the second part of your problem, let's see what that says.
02:12
The second part says identify all data points that are considered outliers where z is greater than or equal to plus or minus 3 sigma.
02:22
And so if we look at the z values, we see that the z scores, when i compare them in my chart, that i don't have anything, these z scores, nothing is over 3 standard deviations.
02:40
There's nothing, there are no outliers, no x outliers...