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Minitab Cookbook

By : Isaac A Newton
Book Image

Minitab Cookbook

By: Isaac A Newton

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Minitab Cookbook
Isaac A Newton
Feb, 2014 | 338 pages
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Table of Contents (19 chapters)
Minitab Cookbook
Minitab Cookbook
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Worksheet, Data Management, and the Calculator
Worksheet, Data Management, and the Calculator
Introduction
Opening an Excel file in Minitab
Opening data from Access using ODBC
Stacking several columns together
Stacking blocks of columns at the same time
Transposing the columns of a worksheet
Splitting a worksheet by categorical column
Creating a subset of data in a new worksheet
Extracting values from a date/time column
Calculator – basic functions
Calculator – using an if statement
Coding a numeric column to text values
Cleaning up a text column with the calculator
2
Tables and Graphs
Tables and Graphs
Introduction
Finding the Tally of a categorical column
Building a table of descriptive statistics
Creating Pareto charts
Creating bar charts of categorical data
Creating a bar chart with a numeric response
Creating a scatterplot of two variables
Generating a paneled boxplot
Finding the mean to a 95 percent confidence on interval plots
Using probability plots to check the distribution of two sets of data
Creating a layout of graphs
Creating a time series plot
Adding a secondary axis to a time series plot
3
Basic Statistical Tools
Basic Statistical Tools
Introduction
Producing a graphical summary of data
Checking if data follows a normal distribution
Comparing the population mean to a target with a 1-Sample t-test
Using the Power and Sample Size tool for a 1-Sample t-test
Using the Assistant menu for a 1-Sample t-test
Looking for differences in the population means between two samples with a 2-Sample t-test
Using the Power and Sample Size tool for a 2-Sample t-test
Using the Assistant menu to run the 2-Sample t-test
Finding critical t-statistics using the probability distribution plot
Finding correlation between multiple variables
Using the 1 Proportion test
Graphically presenting the 1 Proportion test
Using the Power and Sample Size tool for a 1 Proportion test
Testing two population proportions with the 2 Proportions test
Using the Power and Sample Size tool for a 2 Proportions test
Using the Assistant menu to run a 2 Proportions test
Finding the sample size to estimate a mean to a given margin of error
Using Cross tabulation and Chi-Square
Using equivalence tests to prove zero difference between the mean and a target
Calculating the sample size for a 1-Sample equivalence test
4
Using Analysis of Variance
Using Analysis of Variance
Introduction
Using a one-way ANOVA with unstacked columns
Calculating power for the one-way ANOVA
Using Assistant to run a one-way ANOVA
Testing for equal variances
Analyzing a balanced design
Entering random effects model
Using GLM for unbalanced designs
Analyzing covariance
Analyzing a fully nested design
The repeated measures ANOVA – using a mixed effects model
Finding the critical F-statistic
5
Regression and Modeling the Relationship between X and Y
Regression and Modeling the Relationship between X and Y
Introduction
Visualizing simple regressions with fitted line plots
Using the Assistant tool to run a regression
Multiple regression with linear predictors
Model selection tools – the best subsets regression
Model selection tools – the stepwise regression
Binary logistic regression
Fitting a nonlinear regression
6
Understanding Process Variation with Control Charts
Understanding Process Variation with Control Charts
Introduction
Xbar-R charts and applying stages to a control chart
Using an Xbar-S chart
Using I-MR charts
Using the Assistant tool to create control charts
Attribute charts' P (proportion) chart
Testing for overdispersion and Laney P' chart
Creating a u-chart
Testing for overdispersion and Laney U' chart
Using CUSUM charts
Finding small shifts with EWMA
Control charts for rare events – T charts
Rare event charts – G charts
7
Capability, Process Variation, and Specifications
Capability, Process Variation, and Specifications
Introduction
A capability and control chart report using the capability analysis sixpack
Capability analysis for normally distributed data
Capability analysis for nonnormal distributions
Using a Box-Cox transformation for capability
Using a Johnson transformation for capability
Using the Assistant tool for short-run capability analysis
Comparing the capability of two processes using the Assistant tool
Creating an acceptance sampling plan for variable data
Creating an acceptance sampling plan for attribute data
Comparing a previously defined sampling plan – C = 0 plans
Generating run charts
Generating tolerance intervals for summarized data
Datasets that do not transform or fit any distribution
8
Measurement Systems Analysis
Measurement Systems Analysis
Introduction
Analyzing a Type 1 Gage study
Creating a Gage R&R worksheet
Analyzing a crossed Gage R&R study
Studying a nested Gage R&R
Checking Gage linearity and bias
Expanding a Gage study with extra factors
Studying a go / no go measurement system
Using the Assistant tool for Gage R&R
Attribute Gage study from the Assistant menu
9
Multivariate Statistics
Multivariate Statistics
Introduction
Finding the principal components of a set of data
Using factor analysis to identify the underlying factors
Analyzing consistency of a test paper using item analysis
Finding similarity in results by rows using cluster observations
Finding similarity across columns using cluster variables
Identifying groups in data using cluster K-means
The discriminant analysis
Analyzing two-way contingency tables with a simple correspondence analysis
Studying complex contingency tables with a multiple correspondence analysis
10
Time Series Analysis
Time Series Analysis
Introduction
Fitting a trend to data
Fitting to seasonal variation
Time series predictions without trends or seasonal variations
11
Macro Writing
Macro Writing
Introduction
Exec macros to repeat simple commands
Building a Global macro to create a custom graph layout
Obtaining input from the session window with a Global macro
Creating a Local macro
Local macros with subcommands, submacros, and control statements
Navigating Minitab and Useful Shortcuts
Navigating Minitab and Useful Shortcuts
The Project Manager toolbar
Index
Index

Analyzing a balanced design

A balanced ANOVA is one where all combinations of factors have the same number of observed results.

Here, we will look at the analysis of a designed experiment. The study is on an automobile filter to reduce pollution. This study looks at the noise properties of the filter. The response of the noise level is in decibels. The factors include vehicle size—1 2 3, representing small to large, type of filter—1 representing standard and 2 representing octel, and side—1 representing right and 2 representing left.

We will use a balanced ANOVA to study the effect on the results as all treatment conditions have the same number of observations. The terms in the model will be checked for significance using an alpha of 0.05. All main effects and interactions will be included in the model and we will produce residual plots to check the assumptions of using ANOVA.

Getting ready

The data and story behind this example are available from StatLib at http://lib.stat.cmu.edu/DASL/Stories...

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