Training objectives
- Acquiring technical skills in the use of Minitab.
- Learning and acquiring the skills to use Minitab in performing analyses in the areas of basic statistics, statistical process control (SPC), measurement systems analysis (MSA) and selected statistical process improvement tools (tests, ANOVA, introduction to DOE).
- Learning the tools to facilitate the presentation of the data received.
- Streamlining the company's decision-making processes.
- More effective working of teams implementing improvement projects.
Estimated contribution of the practical part: 80%
Duration: 2 days for 7 h
Programme and exercises
1. Introduction to work with the Minitab software: user interface, data sheets, data types, defining and working with projects, project management (project manager), exporting/importing data, defining user folders, customising toolbars, working with macros, using the Assistant.
2. Basic statistical data analysis - descriptive parameters (measures of position, spread, position, shape), identification of isolated results (Grubbs, Dixon tests), graphical presentation: individual value diagrams, box diagrams, histograms (empirical distribution), empirical vs. theoretical distribution.
3. Normal distribution - three standard deviations rule, graphical test of normality, Anderson-Darling test.
4. Problem-solving tools: Pareto-Lorentz chart, cause-effect diagram, natural tolerance interval.
5. Statistical process control (SPC) - process capability assessment (normal/non-normal distribution), Shewhart control cards (measurable data: cards Xmean-R, Xmean-S, X-MR, alternative assessment - p, np, c, u sheets).
6. Measurement systems analysis (MSA) - evaluation of repeatability and reproducibility (ARM mean and variance method, ANOVA method of analysis of variance), MSA for attribute qualification - consistency of assessments, Cohen’s kappa coefficient.
7. Verification of statistical hypotheses - basic statistical tests - test for the mean, test for comparison of two means, test for variance, test for comparison of two variances, test for the fraction, test for comparison of two fractions.
8. Basics of analysis of ANOVA variance - graphical presentation of variance (multi-vari plot), one-factor ANOVA.
9. Basics of regression and correlation analysis - correlation coefficient, coefficient of determination, linear regression.
10. Introduction to the design of experiments (DOE).
