276-What Every Engineer Should Know About Engineering Probability and Statistics II

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

276-What Every Engineer Should Know About Engineering Probability and Statistics II

The concept of probabilistic design is quite pervasive across all engineering disciplines because of its implication on engineering design decisions. Quite often because of the complexity of the processes and the difficulty in explicating the inherent relationships, assumptions about engineering and other related natural processes are simplified and so do not consider uncertainties inherent in those processes and phenomenon. Safety factors and safety margins have often been employed to overcome the need for probabilistic designs. Under certain circumstances such assumptions may suffice. However, in the realm of engineering design, such assumptions and simplifications may not be acceptable as uncertainties are unavoidable in almost all engineering analyses and design activities. Therefore any recommendation developed without proper identification and assessment of the inherent risks and uncertainties would not only be invalid but would paint an unrealistic and unrepresentative picture and thus could jeopardize public safety.

This second course in the series focuses on an important area of engineering analyses and design, namely Statistical Inference. Statistical Inference is about how we analyze data and use the information to make decisions about a given engineering problem. The process of explicating the complexities of the data to yield information that would eventually be used to make design or mission decisions is known as inference or more appropriately Statistical Inference. If we examine the relationship between the population and the sample (as we did in the first course) we note that there is sort of a symbiotic (parent-population, offspring-sample) relationship between the two. Probability deals with the population with its parameters (parent values) while Statistical Inference deals with the sample and its statistic (values computed from the sample and used to estimate the population or universe parameters). The following areas would be covered in the course but not necessarily in the order shown:

The Point Estimates for the Mean and the variance.
The Central Limit Theorem (CLT) and its role in estimating parameters of a population.
Sampling distributions for means and variances with variance both known and unknown
Sampling distribution for two means & two variances with variance known and unknown
Point Estimator, Interval Estimators and Tests of Hypothesis
Error of estimation and the effect on sample size (n).
Type I and Type II errors and the effect on ample size n
Confidence Intervals for one means and one variances
Confidence Intervals for two means and two variances

Due to the nature of the materials, a significant number of numerical examples have been included to provide better insight into the materials presented. At the end, the engineer should feel well equipped to explore the important area of Statistical Inference and what it offers with regards to Engineering design decisions.

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

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(4.5) 11 Reviews

Review of: What Every Engineer Should Know About Engineering Probability and Statistics II

George Chollar

09/25/2022

Verified Buyer

Good course with examples. Presented in a manner that is beneficial as a refresher course.

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Review of: What Every Engineer Should Know About Engineering Probability and Statistics II

Charles Perryman

12/04/2021

Verified Buyer

Tough course, but well presented.

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Review of: What Every Engineer Should Know About Engineering Probability and Statistics II

MLD

02/01/2021

Verified Buyer

Challenging

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

Michael Dicker

11/22/2020

Verified Buyer

Excellent course; would like a few more calculations to perform, other than that, very satisfied.

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

Doug Sherman

09/08/2019

Verified Buyer

This was a great learning experience for me. At first I was completely confused about Hypothesis theory. It is still tricky what stating a null hypothesis and hoping it is rejected means. In the end, the paper summarizes many cases of what formulas to use based on what is know about means and variances. A little more discussion of the difference in variance with small samples would have been helpful. I had to get a stitistic book to check this out. Thanks for the experience.

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

John Gabriel

04/13/2019

Course was too comprehensive for me who had only a general P/S course more than 40 years ago. You did a great job of presenting the subject however.

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

Arthur Schmitt

01/11/2019

Verified Buyer

Excellent course. Very thorough.

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

William Foley

07/11/2018

Verified Buyer

. . .

The review comments have been removed because they disclosed answer to test questions.

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

John Skog

01/19/2018

Verified Buyer

While the topics covered were very worthwhile, they required additional research to understand. Some expanded explanations a list of definitions would be helpful. There are some typos in the document that should be correctd.

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

Kurt Bauer

12/31/2017

Verified Buyer

Good review of statistical inference for any engineer.

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276-What Every Engineer Should Know About Engineering Probability and Statistics II

Walter David Bruce, Ph.D., P.E.

10/28/2017

Verified Buyer

Course 276, What Every Engineer Should Know About Engineering Probability and Statistics II, was a good course. It provided a good review, even though I had completed Six Sigma Green Belt training about ten years ago.

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Course Code: 100262-02

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

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