00:01
Okay, so i see that you need help with this problem.
00:02
And it says, great pumpkins.
00:03
When growing giant pumpkins for competitions, growers need to keep track of the weights of the pumpkins while they're growing.
00:09
It's difficult to weigh a large pumpkin before it's harvested.
00:13
So a method has been developed for estimating the weight.
00:16
The grower measures around the pumpkin both horizontally and vertically, then adds the results.
00:21
This is called ott over the top.
00:24
Measurement and is used to predict the weight of the pumpkin.
00:27
Following our ott measurements in, actual weights of the 10 largest pumpkins entered into official competitions in a recent year.
00:37
Compute the least squares regression line of predicting the weight of the ottx, round the slope in the y intercept to at least four decimal places.
00:47
So for a, or i'm sorry, for number one, it wants you to find the least squares regression.
00:53
And so to do that, you have to find the sum of x.
00:57
So if you add up all your otts, then you are going to get 4 ,593.
01:05
And then if you add up all of your ys, you are going to get 1 ,900, i'm sorry, 19 ,8003 .9.
01:15
Then if you add up, so one, two, three, four, five, six, seven, eight, nine, ten.
01:23
And then if you add up, i apologize.
01:26
I, i knew something was wrong when there's 10 values and none of the values are less than 2 ,000, that that was incorrect.
01:35
So the mean of, i'm sorry, the sum of y is 21 ,621 .9.
01:44
Then to get the mean of x, it is 459 .3.
01:51
The mean of y is 2 ,162 .19 .19.
01:56
Then the sum of the sum of the squares of x is 5776 .1 and the sum of the products is 4 ,175 .43.
02:06
Then i have to write my equation in y equals mx plus b form.
02:11
And in order to get your slope or your m, you have to take the sum of the products and divide it by the sum of the squares of x.
02:19
So i'm going to take 4 ,175 .43 and i'm going to divide that by 576 .1...