# Minitab Cookbook

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- Gain an in-depth understanding of data formatting in Minitab
- Understand the steps required to generate great results with tools like regression, ANOVA, and multivariate statistics
- Useful and practical recipes that cover examples from a broad range of topics in Minitab

### Book Details

**Language :**English

**Paperback :**338 pages [ 235mm x 191mm ]

**Release Date :**February 2014

**ISBN :**1782170928

**ISBN 13 :**9781782170921

**Author(s) :**Isaac Newton

**Topics and Technologies :**All Books, Big Data and Business Intelligence, Cookbooks, Enterprise

## Table of Contents

PrefaceChapter 1: Worksheet, Data Management, and the Calculator

Chapter 2: Tables and Graphs

Chapter 3: Basic Statistical Tools

Chapter 4: Using Analysis of Variance

Chapter 5: Regression and Modeling the Relationship between X and Y

Chapter 6: Understanding Process Variation with Control Charts

Chapter 7: Capability, Process Variation, and Specifications

Chapter 8: Measurement Systems Analysis

Chapter 9: Multivariate Statistics

Chapter 10: Time Series Analysis

Chapter 11: Macro Writing

Appendix: Navigating Minitab and Useful Shortcuts

Index

- Chapter 1: 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

- Chapter 2: 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

- Chapter 3: 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

- Chapter 4: 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

- Chapter 5: 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

- Chapter 6: 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

- Chapter 7: 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

- Chapter 8: 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

- Chapter 9: 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

- Chapter 10: Time Series Analysis
- Introduction
- Fitting a trend to data
- Fitting to seasonal variation
- Time series predictions without trends or seasonal variations

- Chapter 11: 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

- Appendix: Navigating Minitab and Useful Shortcuts
- The Project Manager toolbar

### Isaac Newton

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### Sample chapters

You can view our sample chapters and prefaces of this title on PacktLib or download sample chapters in PDF format.

- Import data successfully into Minitab from Excel
- Explore the options for generating amazing charts
- Investigate differences between samples with inferential statistics
- Find the significant relationships in data by analyzing variance and using regression
- Work with control charts to view process variation
- Learn about Capability Analysis in Minitab for both normal and non normal data
- Find trends and seasonality in your data
- Apply Multivariate statistics to observe patterns and relationships across many variables
- Automate tasks using the Minitab Macro language
- Use Gage studies and MSA’s to investigate measurement systems

Minitab has been a statistical package of choice across all numerous sectors of industry including education and finance. Correctly using Minitab's statistical tools is an essential part of good decision making and allows you to achieve your targeted results, while displaying fantastic charts and a powerful analysis will also communicate your results more effectively.

"Minitab Cookbook" will take the mystery out of using Minitab and will simplify the steps to produce great results. This book will be hugely beneficial for anyone who knows what statistics or studies they want to run, but who is unsure about just what button to press or what option to select.

In this book, you will learn how to use data from different sources and will be guided through the basics of graphs as well as the basics of hypothesis tests. You will explore the use of non-linear regression, how to construct complex ANOVAs, and even delve into Multivariate statistics.

"Minitab Cookbook" is a great reference on how to create graphs, generate P-values, and how to put data in order. You will explore the basics of charts as well as into the complex depths of Factor analysis, and you will learn everything from the simplest of t-tests to the complexity of mixed model ANOVA. And finally, for all of you who want to write Macros, this book covers the use of Execs, Global, and Local Macros.

This practical cookbook covers a broad range of topics in an easy-to-understand manner. Step-by-step instructions guide you through even the most complicated of tools in Minitab.

This book is great for anyone who is familiar with statistics and who wants to learn how Minitab works. Whilst you do not need to be an expert in all areas of statistics, you should understand the basics of the chapters you are interested in.