The Minitab® work surface
- Initial steps and tips in Minitab®
- The project manager
- Managing projects
- The navigator, the symbol bars, the menu
- Data input, copy data, stack data, sort data, etc.
- Data types and data formatting
- Generate data with patterns
- Random number generator
Diagrams and graphs: Data visualization
- Producing graphs: the graph menu
- Updating graphs after changing the data set
- Reading, interpreting and editing graphs
- Types of graphs: Scatter plot, matrix plot, histogram, dot plot, single value plot, error bar plot, box whisker plot, bar chart, pie charts, 3D charts, etc.
- Formatting graphs
- Producing graphs with grouping variables
Fundamentals of data analysis
- Investigation of the data structure
- Calculating and interpreting descriptive statistics: Location parameters (mean, mode, median) and scatter parameters (range, variance, standard deviation)
- Normal distribution: When are data normally distributed? How does the user make use of this knowledge? How can we find this out quickly and easily? What does it mean if data are not normally distributed?
- How can outliers be detected quickly and easily? How should we handle outliers?
Data from other programs
- Importing data from other applications
- Dynamic link with Excel
Simple hypothesis tests
- Test for mean values
- Scatter test
- Chi² test
- What is significance?
- The p-value
- Simple regression analysis
Example files are handed out to all participants at the start of the seminar (via email). The examples are practical and originate either from literature or from the trainer’s professional experience. The evaluation of example files from the practical experience of training participants is welcome (confidential data should be anonymized in advance).
Objective “Minitab®– Training | Seminar”
Participants learn the basic functionalities of Minitab®. The focus is on the safe handling of the Minitab® user interface, the creation of meaningful diagrams and the handling of statistical data from production, research and QA, e.g. within the scope of improvement- or Six Sigma projects. Participants should be able to import and prepare data and independently create diagrams and evaluations.
- 2 days
- Comprehensive training documents
- Trainers with practical experience
- Confirmation of participation and qualification
- Plenty of opportunities to share experiences and transfer knowledge
- Option to edit participant records
- Professional data analysis through user-friendly interfaces
- Creation of easy-to-interpret graphics, for complex data sets too
- Evaluation of data sets using statistical measures
- Safe differentiation between apparent and true effects
- Use of available data for process optimization