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Predictive Analytics with SAS and R : Core Concepts, Tools, and Implementation / by Ramchandra S Mangrulkar, Pallavi Vijay Chavan.

O'Reilly Online Learning: Academic/Public Library Edition Available online

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Format:
Book
Author/Creator:
Mangrulkar, Ramchandra S.
Contributor:
Vijay Chavan, Pallavi.
Series:
Professional and Applied Computing Series
Language:
English
Subjects (All):
Predictive analytics.
SAS (Computer program language).
R (Computer program language).
Artificial intelligence.
Physical Description:
1 online resource (175 pages)
Edition:
1st ed. 2025.
Place of Publication:
Berkeley, CA : Apress : Imprint: Apress, 2025.
Summary:
Gain practical knowledge of application implementation using various programming approaches in predictive analytics. This book serves as a comprehensive guide for both beginners and professionals in the field of predictive analytics, offering core principles and practical insights without requiring an extensive mathematics or statistics background. The book starts with an introduction to analytics in decision making, protective analytics basics, and implementation in various industries. The book then takes you through types of regression, and simple linear regression in detail, followed by a demonstration of R Studio and SAS. Multiple Linear Regression is discussed next along with MLR model diagnostics. The book covers Multivariate Analysis and teaches you how to work with Principal Components Analysis, Factor Analysis, and much more. You also learn Time series Analysis with an understanding of Autoregressive Moving Average (ARMA) Models. After reading the book, you will be able to put predictive analytics principles into practice. What You Will Learn Understand modeling, estimating, and evaluating models for forecasting Implement Partial F-Test and Variable Selection Method Demonstrate each analysis model in R Studio and SAS Understand SLR and MLR Analysis models .
Contents:
Chapter 1 Introduction to Analytics
Chapter 2 Simple Linear Regression
Chapter 3 Multiple Linear Regression
Chapter 4 Multivariate Analysis and Prediction
Chapter 5 Time Series Analysis.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
9798868809057
OCLC:
1492339314

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