List of all IE courses

4 Credits
Available Fall term

ST 314
or equivalent statistical material
David Kim
424 Rogers Hall

Course Description

Control of quality through the use of statistical analysis; typical control techniques and underlying theory. Development of reliability models and procedures for product assurance.


  • Variation, distributions and point estimation
  • Statistical comparisons and inference
  • Control charts: Interpretation and applications
  • Statistical basis for X-bar / R charts
  • OC curves and average run length (ARL)
  • Process capability analysis and Cp, Cpk & Cpm ratios
  • Gauge capability and repeatability/reproducibility studies
  • Fraction nonconforming sample size, OC, ARL
  • Attribute charts for “fraction non-conforming”
  • Constant/variable size charts for nonconformities
  • Cumulative sum control charts
  • EWMA and moving average control charts
  • Acceptance sampling and MIL STD 105E

Learning Outcomes

The student, upon completion of this course, will be able to:

  1. Present a numerical and graphical characterization of quantitative data. Assuming the quantitative data are observations from a normal distribution compute the probability of specific numerical outcomes. Construct and interpret normal probability plots of quantitative data.
  2. Assuming quantitative data are observations from a normal distribution, form hypotheses pertaining to the mean and variance of the distribution. Reject or do not reject the hypotheses based on appropriate statistical tests for a specified type 1 error probability. Compute and/or explain the procedure for finding the type 2 error level for the statistical tests.
  3. Construct, implement and interpret X-bar and R control charts for variables from standards and from data; and demonstrate how to use the corresponding OC curves.
  4. Construct, implement and interpret p, c, and u control charts for attributes from standards or data; and demonstrate how to use the corresponding OC curves.
  5. Perform a gauge capability study -  calculating the components of varability due to product, measurement error and its’ components (repeatability and reproducibility of the gauge).