# Problem at Work with Regression

1. Apr 12, 2010

### Diffy

Hi

I've been tasked with making a sort of sensitivity analysis tool. The goal was to get as many parameters as possible and then use them to build a model that would allow users to change variables a bit and see what happens to the one dependent variable.

So I used a multi variable regression tool to come up with a single equation:

y = c1*x1 + c2*x2 + ... + cn*xn

Here c's are the calculated coefficients, x's are the independent variables and y is the one dependent value.

Then what I did was I built at tool that allowed the users to adjust the variables they wanted to adjust to see how that changes y. The problem is that when some variables are adjusted up, it makes y go down which does make much sense in our business model.

So I have a few questions
1) Should I be using a different type of regression?
2) Is there a better way to go about this?
3) Are there ways to influence the coefficients I calculate?

Please let me know if additional info is needed.
R^2 = .978
F = 93.967

2. Apr 14, 2010

### Diffy

So maybe I will try asking in a different way since I did not get any responses yet.

I want to build a model based on variables to predict a value, but my variables are have very little correlation to the value I want to predict. What I mean by this is when I look at scatter plots of my variable versus the values I want to predict there is no immediately obvious best fit line, the graphs are truly scattered!

Is there even a way to build an accurate model?

3. Apr 14, 2010