Experimental Design and Industrial Statistics - I


The four-level sequence of courses in this series is intended to provide engineering, technical, and manufacturing personnel with an in-depth and working knowledge of industrial statistics and experimental design methods and techniques. Various aspects of this sequence combine to provide the most unique series of its type in the country, specifically:

  • There are no prerequisites to initiating the series, and the participants are assumed to enter the first course in the series with no prior knowledge of statistical theory;
  • The course sequence stresses applied versus theoretical methods and tools;
  • The course uses over 85 industrial examples and data sets to explore the tools and methods taught, all of which have been gathered in actual industrial applications; and
  • The course sequence is computer-based, to allow for the maximum amount of content to be covered, and ensures that participants will be capable of applying the knowledge and skills acquired in their own positions after the course sequence is successfully completed.

Participants completing the course sequence will be capable of properly gathering and analyzing data, as well as correctly designing and executing experiments in the industrial setting.

Time Requirement

5 days

Number of Participants

A maximum of 45 participants is recommended for this course sequence, with no more than two participants assigned to each computer.



Primary Resource Materials

Experimental Design and Industrial Statistics — Level I manual

Content Outline

  • Frequency Distributions
    • Ungrouped, Relative, and Grouped Frequency Distributions
    • Frequency Polygons and Histograms
  • Descriptive Statistics
    • Measurement Scales
    • Descriptive Measures of Frequency
    • Formulas and Calculations
  • Introduction to Probability
    • Types of Probability
    • Probability Rules/Conditions
  • Probability Distributions
    • Definitions and Configuration
    • Random Variables
    • The Binomial and Poisson Distribution
    • The Normal and Log-Normal Distributions
    • The Exponential Distribution
    • The Weibull Distribution
  • Sampling and Sampling Distributions
    • Populations/Processes and Random Sampling
    • Types of Sampling
    • Random Sampling Distributions and Statistical Inference
  • Estimation
    • Types and Criteria of Estimators
    • Point and Interval Estimates
    • Confidence Levels and Intervals
  • Hypothesis Testing
    • Assumptions and Concepts
    • Testing Hypotheses
    • The Significance Level and Risk
    • One- and Two-Tailed Tests
  • Error and Power in Hypothesis Testing
    • Type I and II Error and Power
    • Calculating Type II Error and Power
  • Sample Size Calculations
    • Factors to be Considered
    • Associated Formulas
    • Relationship of Error, Power, n, Variance, and Effect Size on Sample Size


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