Regression and Modeling the Relationship between X and Y | Minitab Cookbook

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Minitab Cookbook

By : Isaac A Newton

4.4 (8)

Minitab Cookbook

4.4 (8)

By: Isaac A Newton

Overview of this book

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

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

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

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

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

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

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

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

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

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

Time Series Analysis

Time Series Analysis

Introduction

Fitting a trend to data

Fitting to seasonal variation

Time series predictions without trends or seasonal variations

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

Binary logistic regression

Logistic regression models allow us to fit a regression model to categorical data. Here, we will look at the survival rates of passengers on the Titanic. This data is binomial in that we list the survivors or casualties of the disaster.

We will initially recode the Survival columns to state 1 as survived and 0 as casualty. Then, we study the effects of age, class, and gender on the chances of survival. This isn't essential but can be a useful aid to the interpretation of the results.

The final steps will store the event probability calculated from the fitted model to plot the results in a scatterplot.

Getting ready

The data is contained in test format at the StatSci website. The direct link to the Titanic data is as follows:

http://www.statsci.org/data/general/titanic.txt

The data will copy and paste directly into Minitab. The data columns are listed as Passenger class, Age, Gender, and Survival.

Do make sure that you check the dataset, as a couple of passenger details...

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