391-What Every Engineer Should Know About Regression Analyses

By: O. Geoffrey Okogbaa, Ph.D., PE

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Course Objective

This continuing education course is written specifically for professional engineers with the objective of relating to and enhancing the practice of engineering.

Course Description

391-What Every Engineer Should Know About Regression Analyses

Modern computing technologies and Big data have significantly changed the discourse on data mining and data efficacy. In any system where quantities change, it is of interest to look at the effects if any, of the system variables. Indeed, there may be a relationship (in our case statistical relationship) which may be approximated by a simple mathematical relationship. At other times, the mathematical or functional relationship may be complicated. Still there may be situations where there does not seem to be meaningful relationships between the variables and yet we might want to express or relate those variables by some sort of mathematical equations.

Regression Analysis is one of the most important statistical techniques used for data mining applications. It is a statistical methodology that helps estimate the strength and direction of the relationship between two or more variables, more specifically regressor and response variables and provides detailed insight that can be applied to further improve system outcomes. The importance of regression analysis lies in its singular focus on data which means numbers and figures that ultimately define a business entity. In Regression Analyses, two types of variables are of major concern, namely the regressor or predictive variables also known as independent variables, and the response variable.

The independent or predictor variable is one that is not random but is controlled (sometimes observed such as the amount of rainfall on a plot of land when the interest is on the effect of rainfall on crop yield) during an experiment. The dependent or response variable cannot be controlled but is rather measured as an outcome of the manipulation (or observation in the case of rainfall) of the independent variable and thus is a random variable. In this course, we will focus primarily on the following elements of Regression Analyses, namely:

Parameters & Estimates
Probability Distribution of the Parameters
Covariance between two variables
Simple hypothesis tests involving parameters including one- and two-sided t and F tests
Confidence Interval for the parameters
Orthogonal Columns, Diagonal and Symmetric Matrices
Estimation of model R2, Adjusted R2, (?? or r) to assess data efficacy
Coefficient of Variation (CV)
Multicollinearity and Variance Inflation Factors

Questions about this course? Email the Author: okogbaa@aol.com

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(4.2) 4 Reviews

Review of: What Every Engineer Should Know About Regression Analyses

Lawyer C Jolley

11/16/2021

Verified Buyer

Found this course hard to follow even though I was fairly well versed in Regression Analysis. Had I not had a grasp of the subject already, I would not have been able to complete this one. It may be because I don't do this everyday. Might want to consider a slight rework to make easier for an engineer that don't do regression analysis often to follow.

2 of 2 customers found this helpful.

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Review of: What Every Engineer Should Know About Regression Analyses

Joe Stillman

08/27/2021

Verified Buyer

Test worksheet and on-line test had different choices on them. I got some answers wrong because of the mis-match. You can't just copy your worksheet answers into the computer.

1 of 1 customers found this helpful.

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Review of: What Every Engineer Should Know About Regression Analyses

David Stolpa

01/30/2021

Verified Buyer

The best overview of the subject material I have found to date

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391-What Every Engineer Should Know About Regression Analysis

Richard Fletcher

12/16/2020

Verified Buyer

Overall a good review of regression basics. There were a few typos in the test, but everything was promptly corrected by Prof Okogbaa and SunCam.

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Course Code: 100262-09

Course PDH Hours: 5

Engineering Course Approvals

This course is accepted for engineering continuing education credit in all US states, territories, the District of Columbia, and Canadian provinces.
Ohio rules allow only 6-hours of unsupervised online courses such as this course per license renewal period
Kansas rules allow only 5-hours of self-study courses such as this course per license renewal period

About Course Approvals