{"product_id":"discovering-statistics-using-r-9781446200452","title":"Discovering Statistics Using R","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eKeeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, \u003cstrong\u003eDiscovering Statistics Using R\u003c\/strong\u003e 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.\u003c\/p\u003e  \u003cp\u003eThe 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 unde\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eIn statistics, R is the way of the future. 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. \u003c\/p\u003e\u003cp\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eI 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.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\u003cb\u003eTake, 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 related---and are really the same thing---as 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.\u003c\/b\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\u003cb\u003e\u003cb\u003e\u003ci\u003e\u003cbr\u003e\u003cb\u003eProf. Neil Stewart\u003cbr\u003eWarwick University\u003c\/b\u003e \u003c\/i\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\u003cb\u003e\u003cb\u003e\u003ci\u003eField′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. \u003c\/i\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\u003cb\u003e\u003cb\u003e\u003ci\u003e\u003cb\u003e\u003ci\u003e\u003cbr\u003e\u003cb\u003eDr Marcel van Egmond\u003cbr\u003e University of Amsterdam\u003c\/b\u003e \u003c\/i\u003e\u003c\/b\u003e\u003c\/i\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\u003cb\u003e\u003cb\u003e\u003ci\u003e\u003cb\u003e\u003ci\u003eProbably the wittiest and most amusing of the lot (no, really), this book takes yet another approach: it is 958 pages of R-based stats wisdom (plus online accoutrements)... 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.) soon stop feeling like a gimmick, and help to break up the text with useful snippets of stats wisdom. It is very mch a student textbook but it is brilliant... Field et al. is the complete package.\u003cb\u003e\u003ci\u003e\u003cbr\u003e\u003cb\u003eDavid M. Shuker\u003cbr\u003e AnimJournal of Animal Behaviour\u003c\/b\u003e \u003c\/i\u003e\u003c\/b\u003e\u003c\/i\u003e\u003c\/b\u003e\u003c\/i\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e\u003cbr\u003e\"\u003cem\u003eThis work should be in the library of every institution where statistics is taught. It contains much more content than what is required for a beginning or advanced undergraduate course, but instructors for such courses would do well to consider this book; it is priced comparably to books which contain only basic material, and students who are fascinated by the subject may find the additional material a real bonus. The book would also be very good for self-study. Overall, an excellent resource\u003c\/em\u003e.\" -- R. Bharath * Choice *\u003cbr\u003eThe main strength of this book is that it presents a lot of information in an accessible, engaging and irreverent way. The style is informal with interesting excursions into the history of statistics and psychology. There is reference to research papers which illustrate the methods explained, and are also very entertaining. The authors manage to pull off the Herculean task of teaching statistics through the medium of R... All in all, an invaluable resource. -- Paul Webb\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eWhy 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\t    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 tell me?    Packages used in this chapter    Looking at differences    The t-test    The independent t-test    The dependent t-test    Between groups or repeated measures?    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 Several Means: ANOVA (GLM 1)    What will this chapter tell me?    The theory behind ANOVA    Assumptions of ANOVA    Planned contrasts    Post hoc procedures    One-way ANOVA using R    Calculating the effect size    Reporting results from one-way independent ANOVA    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 Analysis of Covariance, ANCOVA (GLM 2)    What will this chapter tell me?    What is ANCOVA?    Assumptions and issues in ANCOVA    ANCOVA using R    Robust ANCOVA    Calculating the effect size    Reporting results    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 Factorial ANOVA (GLM 3)    What will this chapter tell me?    Theory of factorial ANOVA (independant design)    Factorial ANOVA as regression    Two-Way ANOVA: Behind the scenes    Factorial ANOVA using R    Interpreting interaction graphs    Robust factorial ANOVA    Calculating effect sizes    Reporting the results of two-way ANOVA    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 Repeated-Measures Designs (GLM 4)    What will this chapter tell me?    Introduction to repeated-measures designs    Theory of one-way repeated-measures ANOVA    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    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 Mixed Designs (GLM 5)    What will this chapter tell me?    Mixed designs    What do men and women look for in a partner?    Entering and exploring your data    Mixed ANOVA    Mixed designs as a GLM    Calculating effect sizes    Reporting the results of mixed ANOVA    Robust analysis for mixed designs    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 Non-Parametric Tests    What will this chapter tell me?    When to use non-parametric tests    Packages used in this chapter    Comparing two independent conditions: the Wilcoxon rank-sum test    Comparing two related conditions: the Wilcoxon signed-rank test    Differences between several independent groups: the Kruskal-Wallis test    Differences between several related groups: Friedman′s ANOVA    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 Multivariate Analysis of Variance (MANOVA)    What will this chapter tell me?    When to use MANOVA    Introduction: similarities and differences to ANOVA    Theory of MANOVA    Practical issues when conducting MANOVA    MANOVA using R    Robust MANOVA    Reporting results from MANOVA    Following up MANOVA with discriminant analysis    Reporting results from discriminant analysis    Some final remarks    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 Exploratory Factor Analysis    What will this chapter tell me?    When to use factor analysis    Factors    Research example    Running the analysis with R Commander    Running the analysis with R    Factor scores    How to report factor analysis    Reliability analysis    Reporting reliability analysis    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 Categorical Data    What will this chapter tell me?    Packages used in this chapter    Analysing categorical data    Theory of Analysing Categorical Data    Assumptions of the chi-square test    Doing the chi-square test using R    Several categorical variables: loglinear analysis    Assumptions in loglinear analysis    Loglinear analysis using R    Following up loglinear analysis    Effect sizes in loglinear analysis    Reporting the results of loglinear analysis    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 Multilevel Linear Models    What will this chapter tell me?    Hierarchical data    Theory of multilevel linear models    The multilevel model    Some practical issues    Multilevel modelling on R    Growth models    How to report a multilevel model    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 Epilogue: Life After Discovering Statistics Troubleshooting R Glossary    Appendix    Table of the standard normal distribution    Critical Values of the t-Distribution    Critical Values of the F-Distribution    Critical Values of the chi-square Distribution References","brand":"Sage Publications Ltd","offers":[{"title":"Default Title","offer_id":51040029999447,"sku":"9781446200452","price":229.93,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781446200452.jpg?v=1750945566","url":"https:\/\/bookcurl.com\/products\/discovering-statistics-using-r-9781446200452","provider":"Book Curl","version":"1.0","type":"link"}