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Minitab Cookbook

Isaac Newton

With over 110 practical recipes, this is the ideal book for all statisticians who want to explore the vast capabilities of Minitab to organize data, analyze it, and visualize it with impactful graphs.
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Book Details

ISBN 139781782170921
Paperback338 pages

About This Book

  • 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

Who This Book Is For

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.

Table of Contents

Chapter 1: Worksheet, Data Management, and the Calculator
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
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
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
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
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
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
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
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
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
Fitting a trend to data
Fitting to seasonal variation
Time series predictions without trends or seasonal variations
Chapter 11: Macro Writing
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

What You Will Learn

  • 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

In Detail

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.


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