Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical. Discovering Statistics Using R by Andy Field. Read online, or download in secure PDF or secure EPUB format. Editorial Reviews. Review. In statistics, R is the way of the future. The big boys and girls have eBook features: Highlight, take notes, and search in the book; In this edition, page numbers are just like the physical edition; Length: pages; Enhanced.
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Discovering statistics using SAS by Andy P Field. Discovering eBook: Document. English. Discovering statistics using R by Andy Field · Discovering. Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data. Lecturers - request an e-inspection copy of this text or contact your local SAGE representative to discuss your course pellwillfigalus.gq Andy Fields introductory.
Description Contents Resources Reviews Preview Lecturers - request an e-inspection copy of this text or contact your local SAGE representative to discuss your course needs. Watch Andy Field's introductory video to Discovering Statistics Using R 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.
What will this chapter tell me? What the hell am I doing here? I don't belong here. Initial observation: Generating theories and testing them. Data collection 1: Data collection 2: Analysing data.
What have I discovered about statistics? Key terms that I've discovered. Smart Alex's tasks.
DISCOVERING STATISTICS USING R
Further reading. Interesting real research. Building statistical models. Populations and samples. Simple statistical models.
Going beyond the data. Using statistical models to test research questions. 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.
R Packages Used in This Chapter. R Functions Used in This Chapter. Smart Alex's Tasks. The art of presenting data. Packages used in this chapter. Introducing ggplot2. Graphing relationships: Boxplots box-whisker diagrams. Density plots. Graphing means.
Themes and options.
R packages used in this chapter. R functions used in this chapter.
What are assumptions? Assumptions of parametric data. The assumption of normality.
Testing whether a distribution is normal. Testing for homogeneity of variance.
Correcting problems in the data. 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. An Introduction to regression.
General procedure for regression in R. Interpreting a simple regression. Multiple regression: 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: How to report multiple regression. Categorical predictors and multiple regression. Background to logistic regression. What are the principles behind logistic regression? Assumptions and things that can go wrong. Binary logistic regression: How to report logistic regression.
Testing assumptions: The big boys and girls have known this for some time: There are now millions of R users in academia and industry. R is free as in no cost and free as in speech. Andy, Jeremy, and Zoe's book now makes R accessible to the little boys and girls like me and my students. Soon all classes in statistics will be taught in R. I have been teaching R to psychologists for several years and so I have been waiting for this book for some time.
The book is excellent, and it is now the course text for all my statistics classes.
I'm pretty sure the book provides all you need to go from statistical novice to working researcher. Take, for example, the chapter on t-tests.
The chapter explains how to compare the means of two groups from scratch. It explains the logic behind the tests, it explains how to do the tests in R with a complete worked example, which papers to read in the unlikely event you do need to go further, and it explains what you need to write in your practical report or paper.
Discovering Statistics Using R
But it also goes further, and explains how t-tests and regression are relatedand are really the same thingas part of the general linear model. Bitte geben Sie Daten ein: Name oder Pseudonym. Ort optional. Bewertung abgeben. Mehr entdecken aus dem Bereich. Flexible Regression and Smoothing.
Heller; Robert A. Rigby ….
SPSS for Psychologists. Newsletter zum Thema. Kostenlos und Up-to-Date: Sie befinden sich hier:The big boys and girls have known this for some time: If you are freaked out about learning stats, or feel like you don't understand the theory behind how the tests work and when you should perform certain ones, then this book is you.
October 4, Dr Marcel van Egmond University of Amsterdam Probably the wittiest and most amusing of the lot no, really , this book takes yet another approach: it is pages of R-based stats wisdom plus online accoutrements Probably the wittiest and most amusing of the lot no, really , this book takes yet another approach: Please try again later.
Running the analysis with R Commander.
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