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EULA
by Jason Verlen, Andrew Wheeler, Jon Peck, Jesus Salcedo, Keith McCormick
SPSS Statistics for Data Analysis and Visualization
Foreword
Introduction
The Audience for This Book
How This Book Is Organized
How to Use This Book
The Themes of the Book
Understanding the SPSS Bundles and the SPSS Modules
The New SPSS Subscription Bundles
What’s New in SPSS 23 and 24?
Part I: Advanced Statistics
Chapter 1: Comparing and Contrasting IBM SPSS AMOS with Other Multivariate Techniques
T-Test
Factor Analysis and Unobserved Variables in SPSS
AMOS
Chapter 2: Monte Carlo Simulation and IBM SPSS Bootstrapping
Monte Carlo Simulation
Monte Carlo Simulation in IBM SPSS Statistics
Creating an SPSS Model File
IBM SPSS Bootstrapping
Chapter 3: Regression with Categorical Outcome Variables
Regression Approaches in SPSS
Logistic Regression
Ordinal Regression Theory
Ordinal Regression Dialogs
Ordinal Regression Output
Categorical Regression Theory
Categorical Regression Dialogs
Categorical Regression Output
Chapter 4: Building Hierarchical Linear Models
Overview of Hierarchical Linear Mixed Models
Mixed Models…Linear
Mixed Models…Linear (Output)
Mixed Models…Generalized Linear
Mixed Models…Generalized Linear (Output)
Adjusting Model Structure
Part II: Data Visualization
Chapter 5: Take Your Data Visualizations to the Next Level
Graphics Options in SPSS Statistics
Understanding the Revolutionary Approach in The Grammar of Graphics
Bar Chart Case Study
Bubble Chart Case Study
Chapter 6: The Code Behind SPSS Graphics: Graphics Production Language
Introducing GPL: Bubble Chart Case Study
GPL Help
Bubble Chart Case Study Part Two
Double Regression Line Case Study
Arrows Case Study
MBTI Bubble Chart Case Study
Chapter 7: Mapping in IBM SPSS Statistics
Creating Maps with the Graphboard Template Chooser
Chapter 8: Geospatial Analytics
Geospatial Association Rules
Case Study: Crime and 311 Calls
Spatio-Temporal Prediction
Case Study: Predicting Weekly Shootings
Chapter 9: Perceptual Mapping with Correspondence Analysis, GPL, and OMS
Starting with Crosstabs
Correspondence Analysis
Multiple Correspondence Analysis
Applying OMS and GPL to the MCA Perceptual Map
Chapter 10: Display Complex Relationships with Multidimensional Scaling
Metric and Nonmetric Multidimensional Scaling
Nonmetric Scaling of Psychology Sub-Disciplines
Multidimenional Scaling Dialog Options
Multidimensional Scaling Output Interpretation
Subjective Approach to Dimension Interpretation
Statistical Approach to Dimension Interpretation
Part III: Predictive Analytics
Chapter 11: SPSS Statistics versus SPSS Modeler: Can I Be a Data Miner Using SPSS Statistics?
What Is Data Mining?
What Is IBM SPSS Modeler?
Can Data Mining Be Done in SPSS Statistics?
Hypothesis Testing, Type I Error, and Hold-Out Validation
Significance of the Model and Importance of Each Independent Variable
The Importance of Finding and Modeling Interactions
Classic and Important Data Mining Tasks
Chapter 12: IBM SPSS Data Preparation
Identify Unusual Cases
Optimal Binning
Chapter 13: Model Complex Interactions with IBM SPSS Neural Networks
Why “Neural” Nets?
XOR Example Syntax
Neural Net Results with the XOR Variables
Comparing Regression to Neural Net with the Bank Salary Case Study
Chapter 14: Powerful and Intuitive: IBM SPSS Decision Trees
Building a Tree with the CHAID Algorithm
Review of the CHAID Algorithm
CRT for Classification
The Scoring Wizard
Chapter 15: Find Patterns and Make Predictions with K Nearest Neighbors
Using KNN to Find “Neighbors”
The Titanic Dataset and KNN Used as a Classifier
The Trade-Offs between Bias and Variance
Comparing Our Models: Decision Trees, Neural Nets, and KNN
Building an Ensemble
Part IV: Syntax, Data Management, and Programmability
Chapter 16: Write More Efficient and Elegant Code with SPSS Syntax Techniques
A Syntax Primer for the Uninitiated
The Case Study
Chapter 17: Automate Your Analyses with SPSS Syntax and the Output Management System
Overview of the Output Management System
Running OMS from Menus
Automatically Writing Selected Categories of Output to Different Formats
Suppressing Output
Working with OMS data
Running OMS from Syntax
Chapter 18: Statistical Extension Commands
What Is an Extension Command?
TURF Analysis—Designing Product Bundles
Quantile Regression—Predicting Airline Delays
Comparing Ordinary Least Squares with Quantile Regression Results
Support Vector Machines—Predicting Loan Default
Computing Cohen’s d Measure of Effect Size for a T-Test
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Chapter 18: Statistical Extension Commands
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