With an exciting new look, new characters to meet, and its unique combination of humour and step-by-step instruction, this award-winning book is the statistics lifesaver for everyone. From initial theory through to regression, factor analysis and multilevel modelling, Andy Field animates statistics and SPSS software with his famously bizarre examples and activities.
Discovering Statistics Using R D
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'In this brilliant new edition Andy Field has introduced important new introductory material on statistics that the student will need and was missing at least in the first edition. This book is the best blend that I know of a textbook in statistics and a manual on SPSS. It is a balanced composite of both topics, using SPSS to illustrate important statistical material and, through graphics, to make visible important approaches to data analysis. There are many places in the book where I had to laugh, and that's saying a lot for a book on statistics. His excellent style engages the reader and makes reading about statistics fun' - David C Howell, Professor Emeritus, University of Vermont USA
- PowerPoint slides written by the author to accompany chapters of the text. What people are saying - Write a reviewUser ratings5 stars104 stars13 stars02 stars01 star0Reviews aren't verified, but Google checks for and removes fake content when it's identifiedUser Review - Flag as inappropriateReally good book for learning about statistics and how to work with SPSS. Clear, concise and easy to read!
Andy Field is Professor of Child Psychopathology at the University of Sussex. He has published over 70 research papers, 27 book chapters, and 17 books mostly on child emotional development and statistics. He is the founding editor of the Journal of Experimental Psychopathology and has been an associate editor and editorial board member for the British Journal of Mathematical and Statistical Psychology, Cognition and Emotion, Clinical Child and Family Psychology Review and Research Synthesis Methods. His ability to make statistics accessible and fun has been recognized with local and national teaching awards (University of Sussex, 2001; the British Psychological Society, 2007), a prestigious UK National Teaching Fellowship (2010), and the British Psychological Society book award (2006). He adores cats, and loves to listen to and play very heavy music. He lives in Brighton with his wonderful wife Zoë and Fuzzy the cat.
I've been using Discovering... with SPSS... for a couple of years & have just updated to the 5th edition. I LOVE chapter 3, and have actually been covering a lot of that material in my class, so it's nice to have it explicit in the text as well.
"I never thought I would find a statistics textbook amusing but somehow our text pulls it off. I also appreciated the online supplementary tools provided by the publisher. If you haven't seen them yet, you should check them out. They provide a good synthesis of each of the chapters and some easy options to review."
I've had previous editions of this text and as always, I am very impressed with Dr. Fields' humorous approach to statistics. He provides instruction on conducting analyses in the most current version of SPSS and has included Bayesian statistics in the new edition. Students receive comprehensive statistical instruction and many online resources are also provided. This is the best statistics textbook!
"Field has introduced important new introductory material on statistics... This book is the best blend that I know of a textbook in statistics and a manual on SPSS."-David C. Howell, University of Vermont (Emeritus)
Written in his vivid and entertaining style, Andy Field continues to provide students with everything they need to understand, use and report statistics-at every level-in the brand-new Third Edition of Discovering Statistics Using SPSS. Retaining the strong pedagogy from previous editions, he makes statistics meaningful by including playful examples from everyday student life (among other places), creating a gateway into the often intimidating world of statistics. In the process, he presents an opportunity for students to ground their knowledge of statistics through the use of SPSS.To view an electronic walkthrough of this text, click here: NEW to the Third Edition:
discovr_03: Confidence intervals: interactive app demonstrating what a confidence interval is, computing normal and bootstrap confidence intervals using R, adding confidence intervals to data summaries
discovr_05: Visualizing data. The ggplot2 package, boxplots, plotting means, violin plots, scatterplots, grouping by colour, grouping using facets, adjusting scales, adjusting positions.
discovr_06: The beast of bias. Restructuring data from messy to tidy format (and back). Spotting outliers using histograms and boxplots. Calculating z-scores (standardizing scores). Writing your own function. Using z-scores to detect outliers. Q-Q plots. Calculating skewness, kurtosis and the number of valid cases. Grouping summary statistics by multiple categorical/grouping variables.
discovr_08: The general linear model (GLM). Visualizing the data, fitting GLMs with one and two predictors. Viewing model parameters with broom, model parameters, standard errors, confidence intervals, fit statistics, significance, Bayes factors and Bayesian estimates (using default priors).
discovr_10: Moderation and mediation. Centring variables (grand mean centring), specifying interaction terms, moderation analysis, simple slopes analysis, Johnson-Neyman intervals, mediation with one predictor, direct and indirect effects, mediation using lavaan.
discovr_11: Comparing several means. Essentially 'One-way independent ANOVA' but taught using a general linear model framework. Covers setting contrasts (dummy coding, contrast coding, and linear and quadratic trends), the F-statistic and Welch's robust F, robust parameter estimation, heteroscedasticity-consistent tests of parameters, robust tests of means based on trimmed data, post hoc tests, Bayes factors.
discovr_12: Comparing means adjusted for other variables. Essentially 'Analysis of Covariance (ANCOVA)' designs but taught using a general linear model framework. Covers setting contrasts, Type III sums of squares, the F-statistic, robust parameter estimation, heteroscedasticity-consistent tests of parameters, robust tests of adjusted means, post hoc tests, Bayes factors.
discovr_13: Factorial designs. Fitting models for two-way factorial designs (independent measures) using both lm() and the afex package. This tutorial builds on previous ones to show how models can be fit with two categorical predictors to look at the interaction between them. We look at fitting the models, setting contrasts for the two categorical predictors, obtaining estimated marginal means, interaction plots, simple effects analysis, diagnostic plots, partial eta-squared and partial omega-squared, robust models and Bayes factors.
discovr_14: Multilevel models. This tutorial looks at fitting multilevel models using the lme4 package. It begins with an optional section on checking and coding categorical variables before moving on to show you how to fit and interpret a multilevel model.
discovr_14_lme: Multilevel models. This tutorial looks at fitting multilevel models using the nlme package. It begins with an optional section on checking and coding categorical variables before moving on to show you how to fit and interpret a multilevel model.
discovr_15: Repeated measures designs. Fitting models for one- and two-way repeated measures designs using the afex package. This tutorial builds on previous ones to show how models can be fit with one or two categorical predictors when these variables have been manipulated within the same entities. We look at fitting the models, setting contrasts for the categorical predictors, obtaining estimated marginal means, interaction plots, simple effects analysis, diagnostic plots, robust models and Bayes factors.
discovr_16: Mixed designs. Fitting models for mixed designs using the afex package. This tutorial builds on previous ones to show how models can be fit with one or two categorical predictors when at least one of these variables has been manipulated within the same entities and at least one other has been manipulated using different entities. We look at fitting the models, setting contrasts for the categorical predictors, obtaining estimated marginal means, interaction plots, simple effects analysis, diagnostic plots, robust models and Bayes factors. 2ff7e9595c
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