Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS Modeler Key Features\[\*\]Get up–and-running with IBM SPSS Modeler without going into too much depth.\[\*\]Identify interesting relationships within your data and build effective data mining and predictive analytics solutions\[\*\]A quick, easy–to-follow guide to give you a fundamental understanding of SPSS Modeler, written by the best in the business

If you ve already had some experience with IBM SPSS Modeler this cookbook will help you delve deeper and exploit the incredible potential of this data mining workbench. The recipes come from some of the best brains in the business.Key FeaturesGo beyond mere insight and build models than you can deploy in the day to day running of your businessSave time and effort while getting more value from your data than ever beforeLoaded with detailed step-...

The fun and friendly guide to mastering IBM’s Statistical Package for the Social SciencesWritten by an author team with a combined 55 years of experience using SPSS, this updated guide takes the guesswork out of the subject and helps you get the most out of using the leader in predictive analysis.Covering the latest release and updates to SPSS 27.0, and including more than 150 pages of basic statistical theory, it helps you understand the mechanics behind t...

Handbook of Statistical Analysis: AI and ML Applications, third edition, is a comprehensive introduction to all stages of data analysis, data preparation, model building, and model evaluation. This valuable resource is useful to students and professionals across a variety of fields and settings: business analysts, scientists, engineers, and researchers in academia and industry. General descriptions of algorithms together with case studies help readers understand technical and business prob...

Practice making sense of data with IBM’s SPSS Statistics softwareSPSS Statistics Workbook For Dummies gives you the practice you need to navigate the leading statistical software suite. Data management and analysis, advanced analytics, business intelligence—SPSS is a powerhouse of a research platform, and this book helps you master the fundamentals and analyze data more effectively. You’ll work through practice problems that help you understand the calcula...

This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t te...

A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis.Key FeaturesUse Microsoft's product Excel to build advanced forecasting models using varied examplesCover range of machine learning tasks such as data mining, data analytics, smart visualization, and moreDerive data-driven techniques using Excel plugins ...

Explore the big data field and learn how to perform data analytics and predictive modelling in STATA Key FeaturesBook DescriptionSTATA is an integrated software package that provides you with everything you need for data analysis, data management, and graphics. STATA also provides you with a platform to efficiently perform simulation, regression analysis (linear and multiple) \[and custom programming. This book covers data management, graphs visualizat...

This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal inferences from small-scale clinical studies. The macros and example data are provided on the book’s website so that users can run analyses of the text data as well as data from their own studies.The new edition features:...

Extract patterns and knowledge from your data in easy way using MATLABKey FeaturesGet your first steps into machine learning with the help of this easy-to-follow guideLearn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLABUnderstand how your data works and identify hidden layers in the data with the power of machine learning.Book DescriptionMATLAB is the language of ...

This Fifth Edition of Neil J. Salkind’s Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel, presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Opening with an introduction to Excel, including coverage of how to use functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques. New to th...

In SAS Statistics by Example, Ron Cody offers up a cookbook approach for doing statistics with SAS. Structured specifically around the most commonly used statistical tasks or techniques--for example, comparing two means, ANOVA, and regression--this book provides an easy-to-follow, how-to approach to statistical analysis not found in other books. For each statistical task, Cody includes heavily annotated examples using ODS Statistical Graphics procedures such as SGPLOT, SGSCATTER, and SGPAN...