Question about correlation and regression

[abollo]

Hi guys
My question may sound a bit dumb so please excuse me

In regression in data analysis isn't multiple r the coefficient of correlation?
And if so shouldn't the function CORREL yield the same answer if used on the same data sets

Because I tried comparing the number of the data analysis and correl and I got once a positive number in data analysis (0.75) and its equivalent negative number while using correl (-0.75).

Why is that?

Thanks alot

 

[abollo]

anyone?

 

[GooberTron]

Multiple R is generally used when you have more than 1 predictor variable. In the case you only have 1 predictor variable it should be equal to the square root of the RSQ() function, which should also give you the same result as CORREL(). I just tried it on some dummy data and it matched up.

 

[abollo]

Firstly thanks for the reply.

Can you try it with this data?

Empolyment Age	Salary
21	200
18	250
19	500
25	500
19	750
18	1000
18	1000
26	1000
17	2000
18	2000
24	2500
25	2500
19	3500
20	4000
17	5000
18	5000
20	5000
17	5000
17	5000
19	5000
21	5000
25	5000
25	5000
17	6000
21	6000
19	6000
17	7000
21	7000
17	8000
19	8000
29	8000
17	9000
18	9000
19	10000
19	10000
25	10000
20	12000
20	12000
20	13000
25	13000
17	14000
19	15000
24	15000
19	20000
22	20000
19	30000
18	30000
24	30000
18	35000
18	45000

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CORREL gives me -0.07498, while the square root of RSQ gives me 0.07498 and the regression analysis too. Judging from the values and from a scatter diagram I think the relationship is negative

 

[GooberTron]

Yes - but by definition a squared term like the algebraic calculation of RSQ() will only ever return a positive value - so there are two solutions to the square root of RSQ() - a positive and negative value i.e. +/- SQRT(RSQ). This is where CORREL (i.e. before squaring) is helpful in telling you whether your response generally increases or decreases as your predictor variable increases.
Also, multiple R is the positive square root of R^2 - so you will only see positive values for it.