Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world.
The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect.
Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.
Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.
Autorentext
Andy Field is Professor of Quantitative Methods at the University of Sussex. He has published widely (100+ research papers, 29 book chapters, and 17 books in various editions) in the areas of child anxiety and psychological methods and statistics. His current research interests focus on barriers to learning mathematics and statistics.
He is internationally known as a statistics educator. He has written several widely used statistics textbooks including Discovering Statistics Using IBM SPSS Statistics (winner of the 2007 British Psychological Society book award), Discovering Statistics Using R, and An Adventure in Statistics (shortlisted for the British Psychological Society book award, 2017; British Book Design and Production Awards, primary, secondary and tertiary education category, 2016; and the Association of Learned & Professional Society Publishers Award for innovation in publishing, 2016), which teaches statistics through a fictional narrative and uses graphic novel elements. He has also written the adventr and discovr packages for the statistics software R that teach statistics and R through interactive tutorials.
His uncontrollable enthusiasm for teaching statistics to psychologists has led to teaching awards from the University of Sussex (2001, 2015, 2016, 2018, 2019), the British Psychological Society (2006) and a prestigious UK National Teaching fellowship (2010).
He's done the usual academic things: had grants, been on editorial boards, done lots of admin/service but he finds it tedious trying to remember this stuff. None of them matter anyway because in the unlikely event that you've ever heard of him it'll be as the 'Stats book guy'. In his spare time, he plays the drums very noisily in a heavy metal band, and walks his cocker spaniel, both of which he finds therapeutic.
Inhalt
Why Is My Evil Lecturer Forcing Me to Learn Statistics?
What will this chapter tell me?
What the hell am I doing here? I don't belong here
Initial observation: finding something that needs explaining
Generating theories and testing them
Data collection 1: what to measure
Data collection 2: how to measure
Analysing data
What have I discovered about statistics?
Key terms that I've discovered
Smart Alex's tasks
Further reading
Interesting real research
Everything You Ever Wanted to Know About Statistics (Well, Sort of)
What will this chapter tell me?
Building statistical models
Populations and samples
Simple statistical models
Going beyond the data
Using statistical models to test research questions
What have I discovered about statistics?
Key terms that I've discovered
Smart Alex's tasks
Further reading
Interesting real research
The R Environment
What will this chapter tell me?
Before you start
Getting started
Using R
Getting data into R
Entering data with R Commander
Using other software to enter and edit data
Saving Data
Manipulating Data
What have I discovered about statistics?
R Packages Used in This Chapter
R Functions Used in This Chapter
Key terms that I've discovered
Smart Alex's Tasks
Further reading
Exploring Data with Graphs
What will this chapter tell me?
The art of presenting data
Packages used in this chapter
Introducing ggplot2
Graphing relationships: the scatterplot
Histograms: a good way to spot obvious problems
Boxplots (box-whisker diagrams)
Density plots
Graphing means
Themes and options
What have I discovered about statistics?
R packages used in this chapter
R functions used in this chapter
Key terms that I've discovered
Smart Alex's tasks
Further reading
Interesting real research
Exploring Assumptions
What will this chapter tell me?
What are assumptions?
Assumptions of parametric data
Packages used in this chapter
The assumption of normality
Testing whether a distribution is normal
Testing for homogeneity of variance
Correcting problems in the data
What have I discovered about statistics?
R packages used in this chapter
R functions used in this chapter
Key terms that I've discovered
Smart Alex's tasks
Further reading
Correlation
What will this chapter tell me?
Looking at relationships
How do we measure relationships?
Data entry for correlation analysis
Bivariate correlation
Partial correlation
Comparing correlations
Calculating the effect size
How to report correlation coefficents
What have I discovered about statistics?
R packages used in this chapter
R functions used in this chapter
Regression
What will this chapter tell me?
An Introduction to regression
Packages used in this chapter
General procedure for regression in R
Interpreting a simple regression
Multiple regression: the basics
How accurate is my regression model?
How to do multiple regression using R Commander and R
Testing the accuracy of your regression model
Robust regression: bootstrapping
How to report multiple regression
Categorical predictors and multiple regression
What have I discovered about statistics?
R packages used in this chapter
R functions used in this chapter
Key terms that I've discovered
Smart Alex's tasks
Further reading
Interesting real research
Logistic Regression
What will this chapter tell me?
Background to logistic regression
What are the principles behind logistic regression?
Assumptions and things that can go wrong
Packages used in this chapter
Binary logistic regression: an example that will make you feel eel
How to report logistic regression
Testing assumptions: another example
Predicting several categories: multinomial logistic regression
What have I discovered about statistics?
R packages used in this chapter
R functions used in this chapter
Key terms that I've discovered
Smart Alex's tasks
Further reading
Interesting real research
Comparing Two Means
What will this chapter …