Sign-In
Cart
Bayes Factors for Forensic Decision Analyses with R
Paperback
Series: Springer Texts in Statistics
Medical ReferenceApplicationsProbability & Statistics
ISBN13: 9783031098413
Publisher: Springer Nature
Published: Nov 1 2023
Pages: 187
Weight: 0.63
Height: 0.42 Width: 6.14 Depth: 9.21
Language: English
Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability--keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics:
- Probabilistic Inference - Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence.
- Decision Making - Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law.
- Operational Relevance - Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context.
Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes' theorem providing the fundamental logical tenet for assessing how new information--scientific evidence--ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist's thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty.
This book would be relevant to students, practitioners, and applied statisticiansinterested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes.
This book is Open Access.
1 different editions
Also available
Bayes Factors for Forensic Decision Analyses with R
Bozza, Silvia
Biedermann, Alex
Taroni, Franco
Hardcover
Also from
Bozza, Silvia
Bayes Factors for Forensic Decision Analyses with R
Bozza, Silvia
Biedermann, Alex
Taroni, Franco
Hardcover
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
Cetinkaya-Rundel, Mine
Wickham, Hadley
Grolemund, Garrett
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
Durfee, Becky
Street IV, W. Scott
Paperback
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
Spiegelhalter, David
Paperback
Forecasting: Principles and Practice, the Pythonic Way
Hyndman, Rob J.
Athanasopoulos, George
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
The Random Universe: How Models and Probability Help Us Make Sense of the Cosmos
Jaffe, Andrew H.
Hardcover
Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies
West, Geoffrey
Paperback
Ai-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Bruce, Peter
Bruce, Andrew
Gedeck, Peter
Paperback
Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results
Hatcher, Larry
Paperback
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Cheng, Ran
Lee, Peter
Yu, James
Hardcover
Schaum's Outline of Probability and Statistics, 4th Edition: 897 Solved Problems + 20 Videos
Schiller, John J.
Srinivasan, R. Alu
Spiegel, Murray R.
Paperback
An Introduction to Statistical Learning: With Applications in R
Hastie, Trevor
James, Gareth
Witten, Daniela
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
Winston, Wayne L.
Nestler, Scott
Pelechrinis, Konstantinos
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
Van Griensven Thé, Jesse
Rosas-Bustos, Jose
Fraser, Roydon Andrew
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
Yip, Jason
Gupta, Nikhil
Paperback
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Downey, Allen B.
Hardcover
Scorecasting: The Hidden Influences Behind How Sports Are Played and Games Are Won
Moskowitz, Tobias
Wertheim, L. Jon
Paperback
AI for Robotics: Toward Embodied and General Intelligence in the Physical World
Imran, Alishba
Gopalakrishnan, Keerthana
Paperback
Time Series Analysis and Its Applications: With R Examples
Stoffer, David S.
Shumway, Robert H.
Hardcover
Large Language Models: A Deep Dive: Bridging Theory and Practice
Somers, Garrett
Kamath, Uday
Keenan, Kevin
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
Tackes, Jeffrey
Joseph, Manu
Paperback
Challenging Mathematical Problems with Elementary Solutions, Vol. II: Volume 2
Yaglom, I. M.
Yaglom, A. M.
Paperback
Learning Statistics with Jamovi: A Tutorial for Beginners in Statistical Analysis
Foxcroft, David
Navarro, Danielle
Paperback
An Introduction to Statistical Learning: With Applications in Python
Witten, Daniela
Hastie, Trevor
James, Gareth
Hardcover
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Cheng, Ran
Lee, Peter
Yu, James
Paperback
Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin
Adam, John a.
Weinstein, Lawrence
Paperback
Deep Learning in Computational Mechanics: An Introductory Course
Weeger, Oliver
Jokeit, Moritz
Herrmann, Leon
Hardcover
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
Mitchell, Andy
Griffin, Lauren Scott
Paperback
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
Friedman, Jerome
Hastie, Trevor
Tibshirani, Robert
Hardcover
Unlocking Dbt: Design and Deploy Transformations in Your Cloud Data Warehouse
Cyr, Cameron
Dorsey, Dustin
Paperback
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
An Introduction to Statistical Learning: With Applications in Python
Witten, Daniela
Hastie, Trevor
James, Gareth
Paperback
Large Language Model Recipes: A Hands-On Guide to Fine-Tuning, Optimization, Deployment, and Real-World Applications
Kaata, Sashi Kiran
Bolla, Bharath Kumar
Subbaiah, Kalpa
Paperback
Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists
Best, Joel
Hardcover
The Design Inference: Eliminating Chance through Small Probabilities
Dembski, William A.
Ewert, Winston
Hardcover
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
R in Action, Third Edition: Data Analysis and Graphics with R and Tidyverse
Kabacoff, Robert I.
Paperback
Enterprise Guide for Implementing Generative AI and Agentic AI: A Practical Guide to Developing, Deploying, and Operationalizing Ai-Driven Application
Bhattacharya, Rahul
Sinha, Vikas
Edward, Shakuntala Gupta
Paperback
Student's Solutions Guide for Introduction to Probability, Statistics, and Random Processes
Pishro-Nik, Hossein
Paperback
Large Language Models: From Theory to Production
Pacheco Aznar, David
Vanegas, Esteban
Noguer I. Alonso, Miquel
Paperback
A Modern Introduction to Probability and Statistics: Understanding Why and How
Dekking, F. M.
Kraaikamp, C.
Lopuhaä, H. P.
Hardcover
Making Statistics Work: Information Theory and Bayesian Inference
Foley, Duncan
Scharfenaker, Ellis
Paperback
The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day
Hand, David J.
Paperback
From Data to Dollars: Getting Started with Data Analytics and AI in Startups
Sidoruk, Piotr
Paperback