Description

Providing complete coverage of advanced research methods and their implementation in R to increase students' confidence with programming techniques and their application to new situations and problems.

• Provides suitable coverage for students looking to develop a more advanced level of competency in analytical techniques and statistics using R
• Gives students a comprehensive picture by covering basic techniques such as nonlinear curve fitting and function optimization, more specialist topics including bivariate and multivariate statistics, Bayesian statistics, and machine learning methods, and content on methods that can be used to improve research practises, including power analysis and reproducible data analysis
• Carefully introduces the R programming language for those who have not encountered it before and builds up to demonstrate how techniques can be implemented using this software
• Includes worked examples of appropriate techniques using R so students can see coding used in context
• Practice questions with answer guidance are supplied in the book while multiple-choice-questions with instant feedback can be accessed online to give students an opportunity to test their understanding
• Also available as an e-book with functionality, navigation features, and links that offer extra learning support