Minitab Essentials

Minitab software - dotplots

and Basic Statistical Analysis

This hands-on Minitab workshop is normally taught in 2 days. This workshop is a prerequisite for all other Minitab software workshops.

All Minitab training workshops use the latest, current version of Minitab, and authorized Minitab training materials.

Decrease the time required for statistical analysis by quickly learning to navigate MINITAB’s user-friendly and customizable environment. Learn how to import/export data and output between MINITAB and various software and database systems. Enhance your ability to create, manipulate, and restructure data. Develop sound statistical approaches to data analysis by learning how to create and interpret a wide variety of graphs and numerical measures useful for quality improvement initiatives. This course focuses on the utilization of these tools as they pertain to applications commonly found in manufacturing, engineering, and business processes.

Tools Covered Include: t-Tests, Proportion Tests, Tests for Equal Variance, Power and Sample Size, Correlation, Simple Linear and Multiple Regression, ANOVA and GLM.

Overview of Minitab Software

  • Minitab file structure; navigating Minitab using Project Manager; Minitab windows, menus, toolbars and StatGuideMinitab software - 9 graphs, tiled;
  • basic graphical and statistical analysis;
  • Accessing multiple worksheets in a project; ReportPad, Related Documents; changing data types;
  • Basic graphs summaries (dotplots, graphical summary); removing incorrect values, updating a graph;
  • descriptive statistics, and interpretation;
  • multiple graph layouts; creating reports; shortcut keys;
  • interpretation of statistical output.

Optional: video on Normal Distribution (from Against All Odds: Inside Statistics series); discussion of distribution identification; 8 ways to identify Normal distribution; discussion of Hypothesis Testing, Truth Tables

Data Entry & Basic Charts

  • Entering data: AutofillMinitab Graphical Summary Chart
  • Pareto and Barcharts; Grouped BarChart
  • updating a graph after worksheet data changes; editing graphs after creation
  • Patterned Data
  • create data collection and sampling plans; generate patterned numeric, text and date/time data; generate random samples from a column of data;
  • Extracting text data from dates; splitting worksheets

Optional: Tree Diagrams to visualize Crossed and Nested designs for sampling plans (eg Measurement System Analysis); Multi-Vari charts to visualize results from crossed and nested datasets.

Basic Data Analysis

  • histograms, dotplots, boxplots, time series plotsMinitab - Time Series Chart
  • Calculate and interpret descriptive statistics
  • Time series plot
  • Histograms; bins; distributions
  • editing graphs; visualizing statistics & summaries
  • Overadjusting a process
  • Sorting data; summarizing data; distribution shapes

Optional: Demonstration of Deming Funnel Experiment – overadjusting a process increases process variability!

Importing and manipulating data

  • open files directly from Excel, Quattro Pro, Lotus, dbase, txt, csv and dat files;Minitab Multi-Vari Chart
  • querying and importing from ODBC database such as Access;
  • previewing files to import; changing column names, data types before import; importing from Excel;
  • calculator; display descriptive statistics; coding data (numeric to text); tallying data; pareto chart;
  • creation and running of Minitab Execs (Minitab Macros).

Optional: video on Central Limit Theorem (from Against All Odds: Inside Statistics series)

One and Two Sample t tests

  • Minitab BoxplotMinitab Boxplot to compare 2 groups
  • testing for Normal distribution
  • Testing a null hypothesis using t-tests and confidence intervals
  • assesing power of a hypothesis test using power analysis
  • testing the difference betwen a process mean and a target value using a one-sample t test
  • testing the difference between two sample means using a two-sample t-test
  • testing the differences between paired observations using a paired t-test
  • boxplots, individual value plots

Optional: videos on Confidence Intervals, paired t-tests (from Against All Odds: Inside Statistics series); review of Truth Tables, development of Null Hypothesis; online demonstration of Confidence Intervals ; discussion of sample size n = f (alpha, beta, sigma, delta)

Proportion Tests

  • power and sample size for a one-proportion test;
  • Using one-proportion test to determine whether a defect rate is different from a target value;
  • Assumptions in a two-proportion test
  • Fisher’s exact test to determine whether two defect rates are different from one another

Optional: discussion of sample size n = f (alpha, beta, p’)

Correlation and Regression

  • Linear regression modelMinitab Linear Regression Model
  • Measuring the degree of linear association between two variables using graphs, statistics, and correlation
  • Modelling the relationship between a continuous reponse variable and one or more predictor variables;
  • Determining the strength of the relationship between a continuous response variable and one or more predictor variables.
  • polynomial regression; quadratic vs linear models
  • Adding Confidence and Prediction intervals.

Optional: testing assumptions of regression by analyzing residuals

Analysis of Variance

  • Test for Equal VariancesMinitab Test for Equal Variance Graph
  • Assesing the power of an analysis of variance using power analysis
  • Comparing group variances using a variance test
  • Comparing means for samples collected at different levels using a general linear model
  • ANOVA with more than one factor
  • Interpration of interaction plots and multiple comparisons.
  • ANOVA: General Linear Model; full and reduced models; main effects and interactions; pairwise comparisons

Optional: discussion on ANOVA using General Linear Model (GLM); clarification of terms: crossed vs nested factors; fixed vs random factors; mixed models; balanced vs unbalanced designs.

Multiple Regression

  • Matrix Plot with SmootherMinitab Matrix Plot
  • Regression analysis with more than one predictor; matrix plots; multiple correlations; fitting a multiple regression model
  • Best subsets regression
  • Handling multicollinearity in a regression analysis.

Practice Exercises

Each workshop participant receives an official Minitab workbook and data files, as well as a certificate for Recertification Units.

See other Minitab Training Courses, comments from previous participants, and some previous clients who have taken Carol Kavanaugh’s workshops!