Use the cars sold table that shows the number of cars sold...

Use the cars sold table that shows the number of cars sold last month by seven employees at Concord Motors and their number of years of sales experience. The data is below and attached. Experience Sales 1 8 2 6 2 7 4 14 5 9 6 13 8 10 Use simple regression analysis to estimate monthly car sales using the number of years of sales experience. The slope (marginal effect) for the regression equation is ________.

Transcript

00:01 So for this problem, we're trying to find our regression equation, the form of y hat equals intercept, beta, not, plus slope, beta, 1, times x.

00:12 Our slope, beta 1, is equal to ssx, or, pardon me, no, it's ssxy, divided by ssxx, and beta not is equal to y bar minus beta 1 times x bar.

00:31 Now, sxy is equal to the sum of the product between each paired x and y value minus 1 over n times the sum of each x value times the sum of each y value.

00:51 And ss xx is going to be equal to the sum of x squared minus 1 over n times the sum of x to the power of 2.

01:03 So to do this, i'm going to set up a table of values where i have x, y, and x squared, and i'm going to try to find what the total of x is, what the total of y is, and what the total of x squared is.

01:20 Now, i'm actually going to do this using xl, just for expediency here.

01:26 So we have our x's and our y's.

01:29 You can add these up by hand, of course, but i'm just using xl to make this quick.

01:35 So we have our sum of all of our x values and the sum of all the y values.

01:42 And for x squared, well, we simply be taking each x value and squaring it.

01:50 So we can see all of our x squareds.

01:57 And why am i not? there we go.

02:00 We can see that the number of observations is equal to seven.

02:04 So we'll take note of that as well.

02:07 So grabbing those, or really what we're concerned with is going to be the totals back in here.

02:18 We can find our ssxy by, well, plugging in all of the data that we have, except for the fact i'm missing one thing that i needed to calculate, which would have been the x times y's, pardon me.

02:33 So we just multiply each x and y value, so we do 1 times 8 and 2 times 6 would be 12 and so on.

02:41 So we have all of our x times y's.

02:44 And now we have, all of the data that we need...

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