# Discussion board reply. 200 words reply to bold.

Initial question:

What types of business situations or problems might best lend themselves to multiple linear regression? What types may not? When do you anticipate using a multiple linear regression model in your postgraduate, professional experience? Explain.

situations that would use multiple linear regression would be
when they want to examine the relationship between two or more
predictor variables and one outcome variable. This concept is
distinct from a simple linear regression. In the case
of simple linear
regression, we have one predictor variable and one outcome
variable.

A time in my professional experience which I would
anticipate using a multiple linear regression model would be in a
situation where I’m conducting research in a mental health agency
and I’ve developed an instrument that measures how well people
adapt to changes in their job, so an adaptability level geared
toward career. I would want to be able to predict this
adaptability with available continuous level predictor variables.
Let’s say the variables I have from these participants are their
age, IQ score and how many hours they’ve spent studying how to
make adaptations in work environments. With these three variables
I want to see how well I can predict that adaptability level or
skill level.

It may be that those variable don’t predict
adaptability at all; none, 1, 2 or all 3 of the variables may or
may not predict that outcome variable. So with these types of
data it would not be unusual for me to perform a multiple linear
regression. The regression would produce a line of best fit
based on the least squares method.

Reference

Render, B.,
Stair, R. M., Hanna, M., & Hale, T. (2015). Quantitative
analysis for management (12th ed.). Upper Saddle River, NJ:
Pearson