Minitab

The "Minitab" course helps to safely handle the surface of the Minitab software and teaches you the basic tool controls.

course objects

Learning and application of:

• various methods to read in and organize the data and to graphically prepare it
• basic statistical evaluation methods, such as hypothesis tests and confidence intervals, ANOVA, correlation and regression
• Review the requirements of statistical tests and sample size estimates and selectivity with Minitab
• practice-oriented examples in order to apply and interpret appropriate graphical and statistical evaluation methods
• the presentation of results in a report, as well as evaluate repetitive analyses automatically via a simple macro.

seminar content

Working with Minitab (covering all course content and days):

• Project setup and project management
• Handling with the project manager and the Minitab file management structure
• Using of program windows, menus, toolbars, data import and data management
• Create and edit graphics
• Creating and interpreting descriptive statistics.

Day 1

• Introduction to MINITAB 18
  • Basic features of Minitab:
    • working with projects, worksheets, assistants,
    • working with graphics and layout editors;
    • inputting, reading and transcoding of data;
    • splitting and stacking of worksheets;
    • create and edit charts;
    • exporting expenses to other applications.
  • project structure,
  • data organization and important commands
• metrological basics
• data collection,
• measurements and scale levels
• Univariate Descriptive Statistics
  • frequency distributions,
  • central dimensions,
  • dispersion measures,
  • default values,
  • graphic representations
• statistical basics
  • Probability and inferential statistics
• graphical representation
  • clearly represent data
  • recognize correlations
• identify patterns in data
  • identify causes of variation to initiate appropriate measures
• basics of hypothesis test
• hypothesis test: continuous data
  • check the null hypothesis with t-tests and confidence intervals
  • evaluate the selectivity of a hypothesis test
  • t-test with one or two samples or paired t-test
• hypothesis test: attributive data
  • test shares of a random sample
  • compare two shares
  • perform Fisher's Exact test
  • perform chi-square test 

Day 2

• analysis of variance (ANOVA)
  • evaluate the selectivity of an analysis of variance
  • prerequisites for performing an analysis of variance
  • General Linear Model (GLM) and multiple comparisons
• bivariate descriptive statistics
  • correlations
  • crosstables
  • scatter diagrams
• probability distributions
  • sample
  • population
  • normal distribution
  • averaging distribution
• correlation and regression
• correlation analysis
• simple linear regression and polynomial regression
• Response Optimizer

Day 3 (OPTIONAL)

• auditor match
  • comparison of error assessments made by different examiners
• SPC and process capability
  • suitability of measuring systems
  • investigation of continuous testing processes: MSA Type I measuring equipment ability
  • investigation of continuous testing processes: MSA type II with operator influence
  • checking the quality of a process and identifying evidence for improvement
• transform data
  • prepare non-normally distributed data in order to carry out statistical analyzes and to assume the normal distribution
• process capability for non-normal distributed data
  • checking the quality of a process and identifying evidence for improvement
• working with control cards for:
  • monitoring of processes
  • taking timely corrective measures.

Full-day exercises and examples on individual topics and efficient data analysis with Minitab.

 

_{* All prices in €; plus VAT, including refreshments and detailed documentation as well as a reference book tailored to the seminar.}