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Data Analysis Using Sas Enterprise Guide

Author: Lawrence S. Meyers
Publisher: Cambridge University Press
ISBN: 0521112680
Size: 58.77 MB
Format: PDF, ePub
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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 tests, one-way chi square, data transformations, multiple regression, analysis of variance, analysis of covariance, multivariate analysis of variance, factor analysis, and canonical correlation analysis. Designed to be used either as a stand-alone resource or as an accompaniment to a statistics course, the book offers a smooth path to statistical analysis with SAS Enterprise Guide for advanced undergraduate and beginning graduate students, as well as professionals in psychology, education, business, health, social work, sociology, and many other fields.

Statistics Using Sas Enterprise Guide

Author: James B. Davis, Ph.D.
Publisher: SAS Institute
ISBN: 1599947242
Size: 40.30 MB
Format: PDF, ePub, Mobi
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Discover how easy it is to perform statistical analysis using the power of SAS Enterprise Guide. Suitable for students new to statistics and to SAS, as well as for experienced professionals, James Davis's Statistics Using SAS Enterprise Guide provides an introduction to the basics of SAS Enterprise Guide and to statistics. Early chapters in this easy-to-follow book address topics such as how to work with data sets (including SAS data sets, data sets in Microsoft Excel, and other formats) and how to perform queries. A separate chapter on descriptive statistics offers a wide range of techniques and multiple presentation options. Later chapters provide detailed discussions (without calculus) of statistical theory and step-by-step examples that illustrate how to apply the appropriate SAS Enterprise Guide tasks, including both complete output and thorough analyses of the results. These chapters present examples of one-sample inference, two-sample inference, analysis of variance, correlation and regression, and table analysis

Basic Statistics Using Sas Enterprise Guide

Author: Geoff Der
Publisher: SAS Institute
ISBN: 1599947153
Size: 40.74 MB
Format: PDF, ePub
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This example-rich guide shows you how to conduct a wide range of statistical analyses with no SAS programming required. For each analysis, one or more real data sets, a brief introduction of the technique, and a clear explanation of the SAS Enterprise Guide output are provided.

Business Analytics Using Sas Enterprise Guide And Sas Enterprise Miner

Author: Olivia Parr-Rud
Publisher: SAS Institute
ISBN: 1629593281
Size: 33.29 MB
Format: PDF, Mobi
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This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. Today’s businesses increasingly use data to drive decisions that keep them competitive. Especially with the influx of big data, the importance of data analysis to improve every dimension of business cannot be overstated. Data analysts are therefore in demand; however, many hires and prospective hires, although talented with respect to business and statistics, lack the know-how to perform business analytics with advanced statistical software. Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner is a beginner’s guide with clear, illustrated, step-by-step instructions that will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. This book is part of the SAS Press program.

Data Mining Using Sas Enterprise Miner

Author: Randall Matignon
Publisher: John Wiley & Sons
ISBN: 0470149019
Size: 19.63 MB
Format: PDF, ePub, Docs
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The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is a part of the Enterprise Miner software with regard to SEMMA design and data mining analysis. Data Mining Using SAS Enterprise Miner introduces readers to a wide variety of data mining techniques and explains the purpose of-and reasoning behind-every node that is a part of the Enterprise Miner software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes in SAS Enterprise Miner v4.3, followed by detailed explanations of configuration settings that are located within each node. Features of the book include: The exploration of node relationships and patterns using data from an assortment of computations, charts, and graphs commonly used in SAS procedures A step-by-step approach to each node discussion, along with an assortment of illustrations that acquaint the reader with the SAS Enterprise Miner working environment Descriptive detail of the powerful Score node and associated SAS code, which showcases the important of managing, editing, executing, and creating custom-designed Score code for the benefit of fair and comprehensive business decision-making Complete coverage of the wide variety of statistical techniques that can be performed using the SEMMA nodes An accompanying Web site that provides downloadable Score code, training code, and data sets for further implementation, manipulation, and interpretation as well as SAS/IML software programming code This book is a well-crafted study guide on the various methods employed to randomly sample, partition, graph, transform, filter, impute, replace, cluster, and process data as well as interactively group and iteratively process data while performing a wide variety of modeling techniques within the process flow of the SAS Enterprise Miner software. Data Mining Using SAS Enterprise Miner is suitable as a supplemental text for advanced undergraduate and graduate students of statistics and computer science and is also an invaluable, all-encompassing guide to data mining for novice statisticians and experts alike.

Predictive Modeling With Sas Enterprise Miner

Author: Kattamuri S. Sarma
Publisher: SAS Institute
ISBN: 1635260388
Size: 45.59 MB
Format: PDF, Kindle
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A step-by-step guide to predictive modeling! Kattamuri Sarma's Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third Edition, will show you how to develop and test predictive models quickly using SAS Enterprise Miner. Using realistic data, the book explains complex methods in a simple and practical way to readers from different backgrounds and industries. Incorporating the latest version of Enterprise Miner, this third edition also expands the section on time series. Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. Topics covered include logistic regression, regression, decision trees, neural networks, variable clustering, observation clustering, data imputation, binning, data exploration, variable selection, variable transformation, and much more, including analysis of textual data. Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner!

Customer Segmentation And Clustering Using Sas Enterprise Miner Second Edition

Author: Randy Collica
Publisher: SAS Institute
ISBN: 1612900925
Size: 48.56 MB
Format: PDF, Kindle
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In Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition, Randy Collica employs SAS Enterprise Miner and the most commonly available techniques for customer relationship management (CRM). You will learn how to segment customers more intelligently and to achieve, or at least get closer to, the one-to-one customer relationship that today's businesses want. Step-by-step examples and exercises clearly illustrate the concepts of segmentation and clustering in the context of CRM. The book is divided into four parts. Part 1 reviews the basics of segmentation and clustering at an introductory level, providing examples from a variety of industries. Part 2 offers an in-depth treatment of segmentation with practical topics such as when and how to update your models and clustering with many attributes. Part 3 goes beyond traditional segmentation practices to introduce recommended strategies for clustering product affinities, handling missing data, and incorporating textual records into your predictive model with SAS Text Miner software. Part 4 takes segmentation to a new level with advanced techniques such as clustering of product associations, developing segmentation scoring models from customer survey data, combining segmentations using ensemble segmentation, and segmentation of customer transactions. Updates to the second edition include four new chapters in Part 4, Chapters 13-16, that introduce new and advanced analytic techniques that can be valuable in many customer segmentation applications. In addition, Chapter 9 has a new section on using the Imputation node in SAS Enterprise Miner to accomplish missing data imputation, compared to PROC MI used in earlier sections of Chapter 9. Also included are business insights and motivations for selection settings and analytical decisions on many of the examples included in this second edition. This straightforward guide will appeal to anyone who seeks to better understand customers or prospective customers. Additionally, professors and students will find the book well suited for a business data mining analytics course in an MBA program or related course of study. You should understand basic statistics, but no prior knowledge of data mining or SAS Enterprise Miner is required. This book is part of the SAS Press program.

Data Preparation For Analytics Using Sas

Author: Gerhard Svolba
Publisher: SAS Institute
ISBN: 1629597902
Size: 16.65 MB
Format: PDF, ePub, Docs
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Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data structures and considerations from a business point of view. The tasks addressed include viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types, using powerful SAS macros to make changes among the various data mart structures, and more!

Introduction To Data Mining Using Sas Enterprise Miner

Author: Patricia B. Cerrito
Publisher: SAS Institute
ISBN: 1599943379
Size: 48.60 MB
Format: PDF, Docs
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If you have an abundance of data, but no idea what to do with it, this book was written for you! Packed with examples from an array of industries, Introduction to Data Mining Using SAS Enterprise Miner provides you with excellent starting points and practical guidelines to begin data mining today. Author Patricia Cerrito encourages you to think of data mining as a process of exploration rather than as a collection of tools to investigate data. In that way, you choose the methods that will extract the most information from your data, and, while there are no right answers to investigating data sets, there are many questions that can be asked to produce meaningful results. Each answer then creates a path that helps you drill down to explore the data fully. It is up to you to determine what is of interest and what is important to analyze.

Sas For Dummies

Author: Stephen McDaniel
Publisher: John Wiley & Sons
ISBN: 9781118044018
Size: 31.38 MB
Format: PDF, ePub
View: 6757
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Created in partnership with SAS, this book explores SAS, a business intelligence software that can be used in any business setting or enterprise for data delivery, reporting, data mining, forecasting, statistical analysis, and more SAS employee and technologist Stephen McDaniel combines real-world expertise and a friendly writing style to introduce readers to SAS basics Covers crucial topics such as getting various types of data into the software, producing reports, working with the data, basic SAS programming, macros, and working with SAS and databases