Regression Equation

[vancottier]

Hello,
Ive generated a multiple regression equation using a tool i got online. It takes a list of dependent variables and a few independant variables and gives me a multiple regression equation. The equation is trying to predict defects in a software program. The dependant variables is defect count

the equation i got is

0.32*Avg analysis hr + -0.12*Avg. Dev hrs + 0.00*Budget + -0.19*Duration + 19.40 (+/- 21.56)
These independant variables are project details.

What im trying to do is put one of the projects details back into the equation and get a value for defects.

My problem is that when i put these values in (to test the equation) i get a value which is no where near the actual defects that that project had. even though this project was used in the actual making of the equation.

Any ideas??

The R squared of this equation is 91%
Standard error is 21.56

[jemidiah]

It looks like you've used a linear regression; perhaps that type of function doesn't fit your data well. In that case, I'd try using a polynomal regression.

Note: I've never taken a statistics course (coming next semester!) so whatever I've picked up has been taught by physicists. They never went into R squared in any detail (chi squared yes, R squared no), and they only glossed over the equation for standard error, so I don't really know how good a fit that is.

My gut tells me it's going to be a bit difficult to find the actual relationship between your variables without graphing it, but you'd need a 4 dimensional graph to see everything at once (you could, however, use 3 of the independent variables and set one constant).