Read online, or download in secure PDF or secure EPUB format. Watch Andy Field's introductory video to Discovering Statistics Using R Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free. Read "Discovering Statistics Using R" by Professor Andy Field available from Using R takes students on a journey of statistical discovery using R, a free. Not free, but good, is "Discovering Statistics Using R from Andy Field, Jeremy : sidi-its.info or if you Google it you can find it for download free .
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Discovering statistics using SAS by Andy P Field. Discovering eBook: Document. English. Discovering statistics using R by Andy Field · Discovering. Editorial Reviews. Review. In statistics, R is the way of the future. The big boys and girls have Download it once and read it on your Kindle device, PC, phones or tablets. $ eBook features: Read with the free Kindle apps (available on iOS, Android, PC & Mac), Kindle E-readers and on Fire Tablet devices. See all . Watch Andy Field's introductory video to Discovering Statistics Using R Statistics Using R takes students on a journey of statistical discovery using R, a free.
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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.
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. So this book offers not just the step-by-step guidance needed to complete a particular test, but it also offers the chance to reach the zen state of total statistical understanding.
Field's Discovering Statistics is popular with students for making a sometimes deemed inaccessible topic accessible, in a fun way. In Discovering Statistics Using R, the authors have managed to do this using a statistics package that is known to be powerful, but sometimes deemed just as inaccessible to the uninitiated, all the while staying true to Field's off-kilter approach.
Probably the wittiest and most amusing of the lot no, really , this book takes yet another approach: A thoroughly engaging, expansive, thoughtful and complete guide to modern statistics. Self-deprecating stories lighten the tone, and the undergrad-orientated 'stupid faces' Brian Haemorrhage, Jane Superbrain, Oliver Twisted, etc. It is very mch a student textbook but it is brilliant Field et al.
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It is great material for teaching and learning, but also a handy reference book for researchers. As an open source software and with a vast supporting community, R is increasingly adopted by researchers.
Discovering Statistics Using R allows a soft transition from other statistical softwares to this open source alternative. This book covers the material we need, with plenty of exercises, accessible explanations. Most importantly, it describes and teaches the R statistics platform integrated with the rest of the text. This textbook is quite thorough, but the overall style of the writing would not land very well to my California audience unfortunately. This textbook is a marvelous tool to get to know not only the basics in statistics, but also some intermediate and complex analyses.
Its structure allows students to grasp concepts, processes and actual uses of the techniques. I can forget about the usual fear experimented by students when starting on a statistics course.
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An excellent way to start using a powerful tool such as R. Chapter One. This book is not available as an inspection copy. Skip to main content. Other Titles in: Download flyer Recommend to Library. 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. 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.
Formats and Editions of Discovering statistics using R [sidi-its.info]
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: Predicting several categories: Looking at differences. The t -test. The independent t -test. The dependent t -test. Between groups or repeated measures? Planned contrasts.
Post hoc procedures. Reporting results. Behind the scenes. Interpreting interaction graphs. Calculating effect sizes. Introduction to repeated-measures designs. One-way repeated measures designs using R. Effect sizes for repeated measures designs. Reporting one-way repeated measures designs. Factorisal repeated measures designs. Effect Sizes for factorial repeated measures designs. Reporting the results from factorial repeated measures designs.
Mixed designs. What do men and women look for in a partner?
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