LEADER 03215nam 22005535 450 001 9910983384903321 005 20251214173753.0 010 $a9798868809057 024 7 $a10.1007/979-8-8688-0905-7 035 $a(CKB)37391184300041 035 $a(MiAaPQ)EBC31892388 035 $a(Au-PeEL)EBL31892388 035 $a(DE-He213)979-8-8688-0905-7 035 $a(OCoLC)1492339314 035 $a(CaSebORM)9798868809057 035 $a(OCoLC-P)1492339314 035 $a(EXLCZ)9937391184300041 100 $a20250128d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPredictive Analytics with SAS and R $eCore Concepts, Tools, and Implementation /$fby Ramchandra S Mangrulkar, Pallavi Vijay Chavan 205 $a1st ed. 2025. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2025. 215 $a1 online resource (175 pages) 225 0 $aProfessional and Applied Computing Series 311 08$a9798868809040 327 $aChapter 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. 330 $aGain 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 . 606 $aPredictive analytics 606 $aSAS (Computer program language) 606 $aR (Computer program language) 606 $aArtificial intelligence 615 0$aPredictive analytics. 615 0$aSAS (Computer program language) 615 0$aR (Computer program language) 615 0$aArtificial intelligence. 676 $a006.3 700 $aMangrulkar$b Ramchandra S$01784395 701 $aVijay Chavan$b Pallavi$01784396 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983384903321 996 $aPredictive Analytics with SAS and R$94316025 997 $aUNINA