Packt+ | Advance your knowledge in tech

0

All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Data Analysis with IBM SPSS Statistics

You're reading from Data Analysis with IBM SPSS Statistics Implementing data modeling, descriptive statistics and ANOVA

Product type Paperback

Published in Sep 2017

Publisher Packt

ISBN-13 9781787283817

Length 446 pages

Edition 1st Edition

Tools

IBM SPSS

Concepts

Data Analysis

Authors (2):

Ken Stehlik-Barry

Anthony Babinec

View More author details

Table of Contents (24) Chapters

Title Page

Credits

About the Authors

Acknowledgement

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Installing and Configuring SPSS FREE CHAPTER

2. Accessing and Organizing Data

3. Statistics for Individual Data Elements

4. Dealing with Missing Data and Outliers

5. Visually Exploring the Data

6. Sampling, Subsetting, and Weighting

7. Creating New Data Elements

8. Adding and Matching Files

9. Aggregating and Restructuring Data

10. Crosstabulation Patterns for Categorical Data

11. Comparing Means and ANOVA

12. Correlations

13. Linear Regression

14. Principal Components and Factor Analysis

15. Clustering

16. Discriminant Analysis

Select cases dialog box

Select Casesprovides several methods to select a subgroup of cases. In the main menu, navigate to Data | Select Cases.

Here is the Select Cases dialog box:

TheSelect radio buttons provide several methods to select a subgroup of cases. The buttons correspond to the following actions:

All cases: Turns case filtering off and uses all cases.
If condition is satisfied: Uses a conditional expression to select cases. If the result of the conditional expression is true, then SPSS Statistics selects the case. If the result of the conditional expression is false or missing, then SPSS Statistics does not select the case.
Random sample of cases: Selects a random sample of cases.
Based on time or case range: Selects cases based on a range of case numbers or a range of dates/times.
Use filter variable: Uses the selected numeric variable as a filter variable. Cases with any value other than 0 or missing for the filter variable are selected.

The Output radio buttons control the treatment...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $15.99/month. Cancel anytime

Authors (2)

Ken Stehlik-Barry

Ken Stehlik-Barry

Kenneth Stehlik-Barry, PhD, joined SPSS as Manager of Training in 1980 after using SPSS for his own research for several years. Working with others at SPSS, including Anthony Babinec, he developed a series of courses related to the use of SPSS and taught these courses to numerous SPSS users. He also managed the technical support and statistics groups at SPSS. Along with Norman Nie, the founder of SPSS and Jane Junn, a political scientist, he co-authored Education and Democratic Citizenship. Dr. Stehlik-Barry has used SPSS extensively to analyze data from SPSS and IBM customers to discover valuable patterns that can be used to address pertinent business issues. He received his PhD in Political Science from Northwestern University and currently teaches in the Masters of Science in Predictive Analytics program there.

See other products by Ken Stehlik-Barry

Anthony Babinec

Anthony Babinec

Anthony J. Babinec joined SPSS as a Statistician in 1978 after assisting Norman Nie, SPSS founder, in a research methods class at the University of Chicago. Anthony developed SPSS courses and trained many SPSS users. He also wrote many examples found in SPSS documentation and worked in technical support. Anthony led a business development effort to find products implementing then-emerging new technologies such as CHAID decision trees and neural networks and helped SPSS customers successfully apply them. Anthony uses SPSS in consulting engagements and teaches IBM customers how to use its advanced features. He received his BA and MA in Sociology with a specialization in Advanced Statistics from the University of Chicago and teaches classes at the Institute for Statistics Education. He is on the Board of Directors of the Chicago Chapter of the American Statistical Association, where he has served in different positions including President.

See other products by Anthony Babinec

Other recommended products

Related to this chapter

IBM SPSS Modeler Essentials

IBM SPSS Modeler Essentials

IBM SPSS Modeler allows quick, efficient predictive analytics and insight building from your data, and is a popularly used data mining tool. This book will guide you through the data mining process, and presents relevant statistical methods which are used to build predictive models and conduct other analytic tasks using IBM SPSS Modeler. From importing the data to finding hidden relationships within it, you will be able to build solid data mining solutions and then deploy them to production. The book also contains valuable information on evaluating and enhancing the performance of your data models.

Dec 2017 7h 56m

Associations and Correlations

Associations and Correlations

Through this book, you'll learn why most statistical techniques give incorrect results and what you can do to avoid the most common pitfalls. You'll learn how to make sure you get the correct results the first time, every time.

Jun 2019 4h 28m

Data Analysis with R

Data Analysis with R

R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples.

Mar 2018 19h 0m

SAS for Finance

SAS for Finance

SAS is the ground-breaking tool for advanced, predictive, and statistical analytics. Right from refining your data using power of SAS analytics, you will be able to exploit the capabilities of high-powered package to create accurate financial models. You can easily assess the pros and cons of models to suit unique business needs.

May 2018 10h 12m

R Statistics Cookbook

R Statistics Cookbook

With this book, you will learn to execute a series of intermediate to advanced statistical tasks as you walk through each chapter. You will not only get well versed with the traditional statistics but you will also cover the necessary statistics required for machine learning and deep learning concepts.

Mar 2019 14h 56m

Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

This book is an introduction to data mining and its practical demonstration of working with real-world data sets. With this book, you will be able to extract useful insights using common Python libraries. You will also learn key stages like data loading, cleaning, analysis, visualization to build an efficient data mining pipeline.

Apr 2019 6h 16m

Applied Unsupervised Learning with R

Applied Unsupervised Learning with R

Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and all features of R that enable you to understand your data better and get answers to all your business questions.

Mar 2019 10h 40m

Training Systems using Python Statistical Modeling

Training Systems using Python Statistical Modeling

This book will acquaint you with various aspects of statistical analysis in Python. You will work with different types of prediction models, such as decision trees, random forests and neural networks. By the end of this book, you will be confident in using various Python packages to train your own models for effective machine learning.

May 2019 9h 40m

Statistical Application Development with R and Python

Statistical Application Development with R and Python

Statistical Analysis involves collecting and examining data to describe the nature of data that needs to be analyzed. It helps you explore the relation of data and build models to make better decisions. You will begin with a brief understanding of the nature of data and end with modern and advanced statistical models like CART. Every step is taken with DATA and R code, and further enhanced by Python. By the end of this book you will be able to apply your statistical learning in major domains at work or in your projects.

Aug 2017 14h 24m

MATLAB for Machine Learning

MATLAB for Machine Learning

MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will build a foundation for machine learning using MATLAB for beginners. It will also help you learn regression, clustering, classification, predictive analytics, artificial neural networks, and more with MATLAB.

Aug 2017 12h 44m

Mastering Machine Learning with R

Mastering Machine Learning with R

Machine learning is the field of Artificial Intelligence where we build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2.

Apr 2017 14h 0m

Practical Predictive Analytics

Practical Predictive Analytics

This book teaches six specific steps needed to implement predictive analytics using R. It also teaches how team collaboration is critical and how it increases the chances of implementing a successful model. The book uses cases from healthcare, marketing, and government to build practical skills. Big Data is also covered, in this book, which will extend your skill sets by learning Databricks and RSpark.

Jun 2017 19h 12m

Personalised recommendations for you

Based on your interests and search pattern

Mathematics of Machine Learning

Mathematics of Machine Learning

Deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems with structured guidance. Gain the confidence to engage with advanced ML literature and tailor algorithms to meet your project requirements.

May 2025 24h 20m

Generative AI with Python and PyTorch

Generative AI with Python and PyTorch

Learn how to create images and text using VAEs, GANs, LSTMs, and transformers. Implement applications in natural language processing and computer vision through practical tutorials.

Mar 2025 15h 0m

Practical Generative AI with ChatGPT

Practical Generative AI with ChatGPT

This book helps you unlock ChatGPT's potential to make your working life better. From prompt engineering to creating custom GPTs, you'll enhance your productivity, creativity, and efficiency with practical insights and advanced techniques.

Apr 2025 12h 52m

Generative AI with LangChain

Generative AI with LangChain

Gain a solid foundation in LangChain, agentic AI, and LangGraph, and learn to build production-ready systems with multi-agent architectures, advanced RAG pipelines, Tree of Thought reasoning, agent handoffs, and fine-grained error handling.

May 2025 15h 52m

Architecting Power BI Solutions in Microsoft Fabric

Architecting Power BI Solutions in Microsoft Fabric

Power BI provides several options to solve common data problems, and designing the correct solution for each scenario can be a daunting task. This book makes it easier by guiding you through designing optimal solutions using Power BI.

Apr 2025 14h 16m

Microsoft Identity and Access Administrator SC-300 Exam Guide

Microsoft Identity and Access Administrator SC-300 Exam Guide

This comprehensive guide covers key topics such as Microsoft Entra ID implementation, authentication and access management, external user management, and hybrid identity solutions, providing practical insights and techniques for SC-300 exam success.

Mar 2025 19h 48m

LLM Design Patterns

LLM Design Patterns

This book helps you gain practical skills to develop and deploy LLMs. You'll learn data prep, training, pruning, quantization, and evaluation, as well as explore RAG, advanced prompting, and optimization to build robust, scalable language models.

May 2025 17h 48m

Tableau Cookbook for Experienced Professionals

Tableau Cookbook for Experienced Professionals

Advance your Tableau knowledge beyond the basics, streamline dashboard performance, tackle advanced geospatial challenges, and unlock API potential while fortifying your corporate data infrastructure with proven best practices.

Apr 2025 12h 24m

Time Series Analysis with Spark

Time Series Analysis with Spark

This book offers a complete guide to time series analysis with Apache Spark and Databricks, covering essential concepts and advanced techniques including Generative AI to equip readers with skills for real-world challenges across industries.

Mar 2025 9h 56m

Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT

Transform IoT systems with the power of artificial intelligence using this hands-on guide. Dive into practical techniques and expert insights to innovate and optimize your IoT devices, making them smarter and more efficient.

May 2025 15h 44m