topic Re: Linear Regression Interpreting output in Discussions

Linear Regression Interpreting output

sigi2408 — Sun, 11 Jun 2023 11:19:49 GMT

I have this output and I want to know what is the expected A value when C equals 0.

Don't I just set 0 in the linear equation and get A=2.6? (I've told that the answer is 3.6..)

In addition, does anyone know what is the meaning of: "Calculate the value of the TOTAL"?

Thank you everyone!

Re: Linear Regression Interpreting output

txnelson — Wed, 24 Nov 2021 10:16:14 GMT

Setting A=0 will result in giving you the intercept value, which in your example is 5.5652114

Re: Linear Regression Interpreting output

sigi2408 — Wed, 24 Nov 2021 11:10:53 GMT

Right, so if C=0, A will be 2.6.

And I don't need to relate to the first image? (again..only because I was told that the answer is A=3.6)

Re: Linear Regression Interpreting output

txnelson — Wed, 24 Nov 2021 12:57:50 GMT

I come up with 2.69

Re: Linear Regression Interpreting output

dale_lehman — Wed, 24 Nov 2021 13:42:41 GMT

I don't get 3.6 either. But your bivariate plot does not look linear to me - I think a quadratic would fit better. Did you try that? The value of C when A=0 will be higher than the 2.69 that txnelson calculated. In any case, you should provide a bit more context to your question: what exactly were you asked to do? Was a linear regression a condition for the question?

Re: Linear Regression Interpreting output

P_Bartell — Wed, 24 Nov 2021 16:10:23 GMT

The first image in your post (the histogram) can't be used to determine the value of A when C = 0. You can determine the value of A when C = 0 by solving the regression equation in second image by substituting 0 for C and then algebraically solving the equation 0 = 5.565 - 2.067*A. Or do it the cool way...use the JMP cross hair tool from the tool bar and find the value of A when you put the cross hairs over the red line when C = 0. Either way the answer is 2.69.

Re: Linear Regression Interpreting output

Dan_Obermiller — Wed, 24 Nov 2021 20:45:29 GMT

Or another cool way: Use Fit Model instead of Fit Y by X. then you can use Inverse Prediction. You don't need to do any calculation or guessing with the crosshairs. Plus, you will even get a 95% confidence interval for the possible A value.

Re: Linear Regression Interpreting output

P_Bartell — Wed, 24 Nov 2021 21:38:11 GMT

That's one of the cool things about JMP...very often there are multiple ways to visualize, interpret, and gain insight wrt to data and a problem at hand. One thing I always coached my JMP user friends is "Try them all!" You might find something unique you weren't even looking for! Then the real fun begins:)

Re: Linear Regression Interpreting output

sigi2408 — Thu, 25 Nov 2021 13:13:21 GMT

I got only those two outputs from JMP that according to them I need to answer a few questions.

One of them was to find A when C=0.

I think you are all right and I just wanted to make sure...and tell the professor =]

Thank you!