How do we measure validity in a regression model


Discussion 1: Validity in Regression

When you think about it, putting a regression model together is really not that difficult. After all, I assume if you are doing that you would have a feel for the process you are modeling and the variables to choose for the model. But the real question is "is the model any good"? Here is where measures of validity and reliability come into play. How do we measure validity in a regression model?

Discussion 2: Reliability in Regression

As mentioned in Discussion 1, the issues of validity and reliability are critical when evaluating your regression model. For reliability the most significant issues are serial correlation, heteroscedasticity and collinearity. What are these issues and how do they affect the reliability of our regression model? And how can we spot them if they are there?

Discussion 3: Deming's 14 Points

Quality management has become a major area of concern for almost all organizations. Using tools like Six Sigma they are able to make quality improvements to product and process so important in the modern global marketplace. Almost all of these systems have their roots in the work of W. Edwards Deming. One of the more important elements of Deming's work is his famous 14 points. What are these points, how do they relate to quality and which ones do you find especially important to understand?

The response should include a reference list. Double-space, using Times New Roman 12 pnt font, one-inch margins, and APA style of writing and citations.

Solution Preview :

Prepared by a verified Expert
Operation Management: How do we measure validity in a regression model
Reference No:- TGS02968732

Now Priced at $30 (50% Discount)

Recommended (90%)

Rated (4.3/5)