2^3 Design
Mathews Malnar and Bailey, Inc.

Quality engineering, applied statistical consulting,
and training services for R&D, product, process,
and manufacturing engineering organizations.
Run Chart

An Introduction to MINITAB

Course Description: This hands-on course provides an introduction to statistical methods for quality engineering using MINITAB. Students will learn to enter and manage their data in MINITAB worksheets, create graphical displays of their data, perform basic statistical analyses like confidence intervals, hypothesis tests, ANOVA, and linear regression, and use special methods like designed experiments, gage error studies, process capability studies, and sample size calculations.

Course Format: This course is usually taught in three four-hour sessions with a possible fourth session dedicated to specific customer applications. The course must be taught in a computer lab with one computer per student.

Course Goals: Upon completion of this course students should be able to use MINITAB to:
1.    Enter data into worksheets manually, by copy/paste operations, from Excel or Lotus spreadsheets, and from text files.
2.    Manipulate data and make simple calculations.
3.    Calculate descriptive statistics for sample data.
4.    Calculate probabilities and inverse probabilities for common probability distributions.
5.    Create and edit basic graphical data presentations.
6.    Construct and interpret normal probability plots.
7.    Construct confidence intervals and perform simple hypothesis tests for one and two sample location and variation problems.
8.    Perform hypothesis tests for one and two sample fractions defective.
9.    Create control charts for defectives, defects, and measurement data.
10.    Fit lines and curves to data and plot them.
11.    Use ANOVA to test one- and two-way classification problems for differences between treatments.
12.    Create and analyze a simple factorial designed experiment.
13.    Analyze data from gage error studies.
14.    Analyze data from process capability studies.
15.    Calculate sample sizes for experiments.
16.    Print data, statistical analyses, and graphs.
17.    Store work in project and worksheet files.
18.    Write and execute simple macros.

Prerequisites: This course is intended for students who have practical knowledge of and experience with statistical quality engineering methods but have no or limited experience with MINITAB. Students should have successfully completed a short course in basic statistical methods including:
Students are also expected to have basic Microsoft Windows skills.

Course Outline: Each section includes a short presentation and one or more hands-on exercises:
1.    Overview of the MINITAB Environment
2.    Data Types and Format
3.    Entering and Saving Data
4.    Manipulating Data
5.    Calculations
6.    Descriptive Statistics
7.    Graphs
8.    Calculating Probabilities
9.    Confidence Intervals for Attribute and Variables Data
10.    Tests for Attribute and Variables Data
11.    Statistical Process Control
12.    Analysis of Variance
13.    Linear Regression
14.    Design of Experiments
15.    Gage Error Studies
16.    Process Capability Studies
17.    Reliability/Life Test Data Analysis
18.    Sample Size and Power Calculations
19.    Command Line Operations
20.    MINITAB Macros

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