Statistics Design of Experiments

  • Statistics Design of Experiments

Programs

Start Date
July 10, 2025
Duration
36 Hours

Statistics Design of Experiment

Overview

Design of Experiments (DOE) is a powerful tool that enables you to investigate and manipulate multiple key process input variables concurrently to optimize a specific output or response variable. This course will expose learners to key knowledge required to design and analyse statistical experiments using Minitab. Pre-requisite Basic Statistics with Minitab will be a distinct advantage. However, the first day of the course will be a review of basic statistical concepts relevant to DOE.

 Course Outline

DOE Statistics

  1. Understand key statistical concepts and definitions
    1. Population, sample, types of data , etc
    2. Measures of process variation and central tendency
    3.  Descriptive and inferential statistics.
  2. Understand the distribution of your data
    1. Distribution parameters
    2. Difference between PDF and CDF
    3. Probability Distributions normal, t, binomial, Poisson, F, Chi-square. 9
  3. Review of Statistical Inferences with Minitab
    1. Confidence Intervals.
    2. Hypothesis testing.
    3. Analysis of Variance.
    4. Goodness-of-fit test.
    5. Individual Distribution Identification.
  4. Review of Regression Analysis with Minitab.

 DOE Fundamentals

  1. Understanding DOE terms and concepts
    1. independent and dependent variables,
    2. factors and levels,
    3. treatment, error, replication,
    4. full and fractional designs,
    5. screening experiments,
    6. confounding, etc
    7. covariates and analysis of covariates (ANCOVA).
  2. Experimental Planning
    1. Measurement systems analysis,
    2. Identifying your objectives,
    3. Identifying factors and responses of interest,
    4. Design type selection,
  3. Creating a Design In Minitab
    1. Create a Full Factorial Design,
    2. Understand Design Table,
    3. Modify your design to Fractional Factorial,
    4. Understand Aliasing and Alias Structure.
  4. 11 Manually Analyse A Full Factorial Design
    1. Understand Main Effects,
    2. Understand Interaction Effects,

 Design and Analysis of Experiments

  1. Create and Analyse A Screening Experiment
    1. Definitive Screening Design.
    2. Plackett-Burman Design
      1. Analyse Design Summary,
      2. AnalysePareto Effects, 

AnalyseEffects Plot,

  1. AnalyseMain Effects,
  1. Create and Analyse A Two-level Full Factorial Design
    1. Create and store your design.
    2. Analyse your design using available tools in Minitab Four-in-One plot, probability plot,
      1. ANOVA, Pareto, main and interaction plots, etc
    3. Reduce the model by screening out factors that are not statistically significant.
    4. Optimise your design.
    5. Identify optimum settings using ▪ Contour plot (Plant Flag) ▪ Surface Plot ▪ Response Optimiser
    6. Use your model to make predictions.
  2. Create A Response Surface Design.
    1. Central Composite Design.
    2. Box-Behnken Design.
    3. Response Surface with Categorical factor.

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Statistics Design of Experiments

July 10, 2025