Sign-In
Cart
Predictive Analytics: Parametric Models for Regression and Classification Using R
Hardcover
Series: Wiley Probability and Statistics
Business GeneralDatabasesProbability & Statistics
ISBN13: 9781118948897
Publisher: Wiley
Published: Oct 13 2020
Pages: 384
Weight: 1.90
Height: 1.00 Width: 7.20 Depth: 10.10
Language: English
Provides a foundation in classical parametric methods of regression and classification essential for pursuing advanced topics in predictive analytics and statistical learning
This book covers a broad range of topics in parametric regression and classification including multiple regression, logistic regression (binary and multinomial), discriminant analysis, Bayesian classification, generalized linear models and Cox regression for survival data. The book also gives brief introductions to some modern computer-intensive methods such as classification and regression trees (CART), neural networks and support vector machines.
The book is organized so that it can be used by both advanced undergraduate or masters students with applied interests and by doctoral students who also want to learn the underlying theory. This is done by devoting the main body of the text of each chapter with basic statistical methodology illustrated by real data examples. Derivations, proofs and extensions are relegated to the Technical Notes section of each chapter, Exercises are also divided into theoretical and applied. Answers to selected exercises are provided. A solution manual is available to instructors who adopt the text.
Data sets of moderate to large sizes are used in examples and exercises. They come from a variety of disciplines including business (finance, marketing and sales), economics, education, engineering and sciences (biological, health, physical and social). All data sets are available at the book's web site. Open source software R is used for all data analyses. R codes and outputs are provided for most examples. R codes are also available at the book's web site.
Predictive Analytics: Parametric Models for Regression and Classification Using R is ideal for a one-semester upper-level undergraduate and/or beginning level graduate course in regression for students in business, economics, finance, marketing, engineering, and computer science. It is also an excellent resource for practitioners in these fields.
Also in
Probability & Statistics
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Grolemund, Garrett
Wickham, Hadley
Paperback
AP Statistics Premium, 2027: 9 Practice Tests + Comprehensive Review + Online Practice
Sternstein, Martin, PH. D.
Paperback
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Wickham, Hadley
Grolemund, Garrett
Cetinkaya-Rundel, Mine
Paperback
Graph Paper Composition Notebook: Quad Ruled 5x5, Grid Paper for Students in Math and Science
Wizo, Math
Paperback
Stat 208 Statistical Thinking: A Book for Stat 208 at Virginia Commonwealth University
Street IV, W. Scott
Durfee, Becky
Paperback
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
Spiegelhalter, David
Paperback
Forecasting: Principles and Practice, the Pythonic Way
Athanasopoulos, George
Hyndman, Rob J.
Paperback
Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries
Frost, Jim
Paperback
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
Spiegelhalter, David
Hardcover
How the World Really Works: The Science Behind How We Got Here and Where We're Going
Smil, Vaclav
Paperback
Mastering Claude AI: Practical Journey from First Prompts to Pro with Claude AI
Dickey, Ryan
Paperback
Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies
West, Geoffrey
Paperback
The Random Universe: How Models and Probability Help Us Make Sense of the Cosmos
Jaffe, Andrew H.
Hardcover
Ai-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Gedeck, Peter
Bruce, Peter
Bruce, Andrew
Paperback
Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results
Hatcher, Larry
Paperback
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Yu, James
Cheng, Ran
Lee, Peter
Hardcover
Schaum's Outline of Probability and Statistics, 4th Edition: 897 Solved Problems + 20 Videos
Srinivasan, R. Alu
Spiegel, Murray R.
Schiller, John J.
Paperback
An Introduction to Statistical Learning: With Applications in R
James, Gareth
Witten, Daniela
Hastie, Trevor
Paperback
The Only Math Book You'll Ever Need, Revised Edition: Hundreds of Easy Solutions and Shortcuts for Mastering Everyday Numbers
Kogelman, Stanley
Heller, Barbara R.
Paperback
SQL Server 2025 Unveiled: The Ai-Ready Enterprise Database with Microsoft Fabric Integration
Ward, Bob
Paperback
How the World Really Works: The Science Behind How We Got Here and Where We're Going
Smil, Vaclav
Hardcover
Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, Second Edition
Nestler, Scott
Pelechrinis, Konstantinos
Winston, Wayne L.
Paperback
Building Large Language Models from Scratch: Design, Train, and Deploy Llms with Pytorch
Grigorov, Dilyan
Paperback
Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
Harrell Jr, Frank E.
Paperback
Schaum's Outline of Probability, Random Variables, and Random Processes, Fourth Edition
Hsu, Hwei P.
Paperback
Quantum Computing and Quantum Machine Learning for Engineers and Developers
Fraser, Roydon Andrew
Van Griensven Thé, Jesse
Rosas-Bustos, Jose
Hardcover
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Downey, Allen B.
Paperback
Making ChatGPT Work for You: Getting the Most Out of Generative AI as a Non-Techie
Evelyn, Lydia
Paperback
Probably the Best Book on Statistics Ever Written: How to Beat the Odds and Make Better Decisions
Shapira, Haim
Hardcover
Challenging Mathematical Problems with Elementary Solutions, Vol. I: Volume 1
Yaglom, I. M.
Yaglom, A. M.
Paperback
The End of Average: Unlocking Our Potential by Embracing What Makes Us Different
Rose, Todd
Paperback
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Domingos, Pedro
Paperback
Databricks Data Intelligence Platform: Unlocking the Genai Revolution
Gupta, Nikhil
Yip, Jason
Paperback
Scorecasting: The Hidden Influences Behind How Sports Are Played and Games Are Won
Wertheim, L. Jon
Moskowitz, Tobias
Paperback
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Downey, Allen B.
Hardcover
Time Series Analysis and Its Applications: With R Examples
Shumway, Robert H.
Stoffer, David S.
Hardcover
AI for Robotics: Toward Embodied and General Intelligence in the Physical World
Gopalakrishnan, Keerthana
Imran, Alishba
Paperback
Large Language Models: A Deep Dive: Bridging Theory and Practice
Keenan, Kevin
Somers, Garrett
Kamath, Uday
Hardcover
Building Generative AI Agents: Using Langgraph, Autogen, and Crewai
Deshmukh, Gaurav
Taulli, Tom
Paperback
The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of C
McGrayne, Sharon Bertsch
Paperback
Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI
Raschka, Sebastian
Paperback
Modern Time Series Forecasting with Python - Second Edition: Industry-ready machine learning and deep learning time series analysis with PyTorch and p
Joseph, Manu
Tackes, Jeffrey
Paperback
Challenging Mathematical Problems with Elementary Solutions, Vol. II: Volume 2
Yaglom, A. M.
Yaglom, I. M.
Paperback
Learning Statistics with Jamovi: A Tutorial for Beginners in Statistical Analysis
Navarro, Danielle
Foxcroft, David
Paperback
An Introduction to Statistical Learning: With Applications in Python
Hastie, Trevor
James, Gareth
Witten, Daniela
Hardcover
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Yu, James
Cheng, Ran
Lee, Peter
Paperback
Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin
Weinstein, Lawrence
Adam, John a.
Paperback
Deep Learning in Computational Mechanics: An Introductory Course
Herrmann, Leon
Weeger, Oliver
Jokeit, Moritz
Hardcover
Unlocking Dbt: Design and Deploy Transformations in Your Cloud Data Warehouse
Cyr, Cameron
Dorsey, Dustin
Paperback
High-Dimensional Probability: An Introduction with Applications in Data Science
Vershynin, Roman
Hardcover
The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements and Statistics
Griffin, Lauren Scott
Mitchell, Andy
Paperback
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
Tibshirani, Robert
Friedman, Jerome
Hastie, Trevor
Hardcover
ACCUPLACER Math Prep: ACCUPLACER Math Test Study Guide with Two Practice Tests [Includes Detailed Answer Explanations]
Tpb Publishing
Paperback
Observability for Large Language Models: Site Reliability and Chaos Engineering for AI at Scale
Sharma, Ankush
Paperback
Bayesian Analysis with Python - Third Edition: A practical guide to probabilistic modeling
Martin, Osvaldo
Paperback
Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries
Frost, Jim
Hardcover
Prompt Engineering for Everyone: A Self-Taught, Human-Centered Approach to AI Programming
Tavakoli, Hamid
Paperback
Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists
Best, Joel
Hardcover
An Introduction to Statistical Learning: With Applications in Python
Hastie, Trevor
James, Gareth
Witten, Daniela
Paperback
Large Language Model Recipes: A Hands-On Guide to Fine-Tuning, Optimization, Deployment, and Real-World Applications
Subbaiah, Kalpa
Kaata, Sashi Kiran
Bolla, Bharath Kumar
Paperback
The Design Inference: Eliminating Chance through Small Probabilities
Dembski, William A.
Ewert, Winston
Hardcover
R in Action, Third Edition: Data Analysis and Graphics with R and Tidyverse
Kabacoff, Robert I.
Paperback
Practical Generative Ai: From Concept to Deployment: Building and Deploying Ethical AI-Powered Solutions
Singh, Pramod
McKeone, James
Paperback
Enterprise Guide for Implementing Generative AI and Agentic AI: A Practical Guide to Developing, Deploying, and Operationalizing Ai-Driven Application
Edward, Shakuntala Gupta
Bhattacharya, Rahul
Sinha, Vikas
Paperback
Student's Solutions Guide for Introduction to Probability, Statistics, and Random Processes
Pishro-Nik, Hossein
Paperback
A Modern Introduction to Probability and Statistics: Understanding Why and How
Kraaikamp, C.
Lopuhaä, H. P.
Dekking, F. M.
Hardcover
Large Language Models: From Theory to Production
Pacheco Aznar, David
Vanegas, Esteban
Noguer I. Alonso, Miquel
Paperback
Exercises and Projects for The Little SAS Book, Sixth Edition
Ottesen, Rebecca A.
Delwiche, Lora D.
Slaughter, Susan J.
Paperback
Making Statistics Work: Information Theory and Bayesian Inference
Foley, Duncan
Scharfenaker, Ellis
Paperback