00:01
Okay, so i see that you need help with this problem.
00:04
And so for this problem, it wants you to use the data to develop an estimated regression equation that could be used to predict the total cost for the given production volume.
00:15
So in order to do that, you have to find your difference between your x minus the mean of x.
00:21
And you have to then find the difference between your y minus the mean of y.
00:26
And so 400 minus, 175, 400 plus 175.
00:36
So your mean of x is 575.
00:41
Your mean of y is 5 ,616 .67, okay? and so then you're finding the difference between them.
00:54
Then you have to multiply each of the values to get this value.
00:59
Multiply this times this to get this.
01:01
This times this to get this.
01:02
So on and so forth.
01:03
Then you total up your, this column.
01:08
This is known as your sum of your products, okay? and then you take x minus the mean of x, square them, then add them together.
01:16
And this is the sum of the squares of x.
01:18
So then what you're going to do is you're going to take your sum of your products divided by the sum of the squares of x.
01:24
And this is going to be your slope.
01:27
Then you're going to take your mean of y, subtract your slope times your mean of x.
01:36
And this is your y intercept.
01:39
So then here is your linear regression equation, okay? and then it says, what is the variable cost in dollars per unit? so this is a.
01:58
And so b, that is 7 .44 is the variable cost...