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Discovering statistics using R

By: Andy Field.
Material type: TextTextISBN: 978-1-4462-0045-2.
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Enhanced descriptions from Syndetics:

The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R. Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is enhanced by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.

Table of contents provided by Syndetics

  • 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 Stats Quiz
  • 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 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 (between-groups)
  • 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