Engineering Statistics

taught by Tom Ryan

The topics covered in this course include prediction intervals, tolerance intervals, calibration intervals, measurement error, accelerated life testing, measurement system appraisal, reliability and lifetime testing.

Those involved in monitoring and testing products and processes in industry.

Engineering Statistics

taught by Tom Ryan

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Engineering Statistics

taught by Tom Ryan

This course goes beyond the standard coverage of introductory statistics to cover topics important to practicing engineers. Participants will learn how to calculate prediction intervals, confidence intervals, and calibration intervals. Participants will also learn to assess measurement error, and measurement system appraisal to determine whether measurement systems are in control. Measurement system appraisal is critical because the results of any statistical analysis will be compromised if there is substantial measurement error. Similarly, designed experiments (not covered in the course) can be seriously undermined when there is measurement error. The course will also cover life testing, accelerated life testing, and reliability testing.

Some familiarity with ANOVA and regression, as covered in Introduction to Statistics 3, will also be helpful. (Also note the comments in the outline, session 4, concerning regression, design of experiments, and sample size and power.)

SESSION 1: Prediction and Tolerance Intervals

• Tolerance intervals
  • 2-sided
  • 2-sided, asymmetric
  • 1-sided, bounded
  • Distribution-free intervals
• Prediction intervals
  • Known parameters
  • Unknown parameters, normality assumed
    • Sensitivity to non-normality
  • Non-normal distributions
    • Single observation
    • Number of failures

SESSION 2: Measurement System Appraisal

• Calibration intervals
• Components of measurement variability
• Tolerance analysis
• Graphical methods
• Bias and calibration

SESSION 3: Reliability and Life Testing

• Repairable and non-repairable populations
• Accelerated testing
  • Arrhenius equation
  • Inverse power function
  • Degradation data and acceleration models
• Censoring
• Distributions and models
  • Exponential
  • Weibull
  • Lognormal
  • Extreme value
• Reliability prediction

SESSION 4: Application of Other Concepts*

• Improving reliability with designed experiments
  • Sample size determination
• Regression
  • Measurement Error
  • Calibration
  • Control

*This section provides engineering applications of concepts that are not fully covered here, but are covered in other statistics.com courses: Introduction Design of Experiments, Regression Analysis, and Sample Size and Power Determination. You will probably get more out of these illustrations if you have previously covered this material, but this is not a course requirement. The examples can also serve to provide meaningful context and motivation for further study.

HOMEWORK:

Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.

This course takes place over the internet at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

The required text for this course is Modern Engineering Statistics (Wiley) by Thomas Ryan, and it can be ordered from Wiley by clicking here. Wiley typically offers statistics.com customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount -- try calling your regional Wiley representative.).

PLEASE ORDER YOUR COPY IN TIME FOR THE COURSE STARTING DATE.

No specific software is required.

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