Quality Engineering Statistics

The tools, theories, and case studies you need to understand the analytical methods of quality engineering

Created by: Ray Harkins, The Manufacturing Academy
Senior Manufacturing Professional, Online Educator

Created by: Michael J. Vella
Instructor with the Manufacturing Academy

What Will I Learn?

• Collecting and summarizing data including type of data, measurement scales, collection methods, visualization techniques, and descriptive statistics
• Statistics and probability terminology and concepts
• Statistical decision making including point estimates, confidence intervals, hypothesis testing, paired comparison tests, goodness of fit tests, ANOVA and more
• Tools for examining the relationships between variables such as linear regression, correlation, and time series analysis.
• Control charting: Objective and benefits, common and special causes, variable charts, attribute charts, interpreting the results, and short run SPC
• Process capability analysis: Pp, Ppk, Cp, Cpk, control limits, specification limits, and interpreting actual histograms and capability indices
• Design and analysis of experiments: Terminology, planning and organizing experiments, replication, balance, order and more; full and fractional factorial
• All topics in the "Quantitative Methods and Tools" section of the ASQ Certified Quality Engineer Body of Knowledge

Requirements

• Basic understanding of manufacturing
• Basic math and spreadsheet skills

Target audience

• Quality engineers, quality technicians, quality managers
• Industrial engineers, manufacturing engineers
• Manufacturing managers, operations managers
• Students studying for the ASQ Certified Quality Engineer exam