Description
Book SynopsisProviding 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.
Trade ReviewUnique in surveying a number of advanced topics, this book is perfectly pitched for advanced undergraduates and above, providing the best introduction to fundamental skill sets in R. * Paul Engelhardt, Associate Professor, School of Psychology, University of East Anglia *
Tricky ideas are grounded and explained well. A very good introduction to R and advanced statistics. * Stephen Hubbard, Honorary Professor of Ecology, School of Social Sciences, University of Dundee *
An extremely clear introduction to methodology in advanced research. The interplay between general explanations and particular illustrative examples is very well done. * Stephen Hubbard, Honorary Professor of Ecology, School of Social Sciences, University of Dundee *
Table of Contents1: Introduction 2: Introduction to the R environment 3: Cleaning and preparing data for analysis 4: Statistical tests as linear models 5: Power analysis 6: Meta-analysis 7: Mixed-effects models 8: Stochastic methods 9: Non-linear curve fitting 10: Fourier analysis 11: Multivariate t-tests 12: Structural equation modelling 13: Multidimensional scaling and k-means clustering 14: Multivariate pattern analysis 15: Correcting for multiple comparisons 16: Signal detection theory 17: Bayesian statistics 18: Plotting graphs and data visualisation 19: Reproducible data analysis
