| Description |
xxiii, 830 pages : illustrations ; 25 cm |
| Contents |
Machine generated contents note: 1.Data, samples and statistics -- 1.1.Chapter overview -- 1.2.What are data? -- 1.3.Samples and populations -- 1.4.Central tendency -- 1.5.Dispersion within a sample -- 1.6.Description, inference and bias -- 1.7.R code for Chapter 1 -- 1.8.Notes on SPSS syntax for Chapter 1 -- 1.9.Bibliography and further reading -- 2.Probability distributions -- 2.1.Chapter overview -- 2.2.Why are probability distributions important in statistics? -- 2.3.Discrete distributions -- 2.4.Continuous distributions -- 2.5.R code for Chapter 2 -- 2.6.Notes on SPSS syntax for Chapter 2 -- 2.7.Bibliography and further reading -- 3.Confidence intervals -- 3.1.Chapter overview -- 3.2.From point estimates to interval estimates -- 3.3.Confidence intervals -- 3.4.Confidence intervals for a difference -- 3.5.Using Monte Carlo methods to estimate confidence intervals -- 3.6.Graphing confidence intervals -- 3.7.R code for Chapter 3 -- 3.8.Notes on SPSS syntax for Chapter 3 -- |
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Contents note continued: 3.9.Bibliography and further reading -- 4.Significance tests -- 4.1.Chapter overview -- 4.2.From confidence intervals to significance tests -- 4.3.Null hypothesis significance tests -- 4.4.t tests -- 4.5.Tests for discrete data -- 4.6.Inference about other parameters -- 4.7.Good practice in the application of significance testing -- 4.8.R code for Chapter 4 -- 4.9.Notes on SPSS syntax for Chapter 4 -- 4.10.Bibliography and further reading -- 5.Regression -- 5.1.Chapter overview -- 5.2.Regression models, prediction and explanation -- 5.3.Mathematics of the linear function -- 5.4.Simple linear regression -- 5.5.Statistical inference in regression -- 5.6.Fitting and interpreting regression models -- 5.7.Fitting curvilinear relationships with simple linear regression -- 5.8.R code for Chapter 5 -- 5.9.Notes on SPSS syntax for Chapter 5 -- 5.10.Bibliography and further reading -- 6.Correlation and covariance -- 6.1.Chapter overview -- |
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Contents note continued: 6.2.Correlation, regression and association -- 6.3.Statistical inference with the product-moment correlation coefficient -- 6.4.Correlation, error and reliability -- 6.5.Alternative correlation coefficients -- 6.6.Inferences about differences in slopes -- 6.7.R code for Chapter 6 -- 6.8.Notes on SPSS syntax for Chapter 6 -- 6.9.Bibliography and further reading -- 7.Effect size -- 7.1.Chapter overview -- 7.2.The role of effect size in research -- 7.3.Selecting an effect size metric -- 7.4.Effect size metrics for continuous outcomes -- 7.5.Effect size metrics for discrete variables -- 7.6.R code for Chapter 7 -- 7.7.Notes on SPSS syntax for Chapter 7 -- 7.8.Bibliography and further reading -- 7.9.Online supplement 1: Meta-analysis -- 8.Statistical power -- 8.1.Chapter overview -- 8.2.Significance tests, effect size and statistical power -- 8.3.Statistical power and sample size -- 8.4.Statistical power analysis -- |
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Contents note continued: 8.5.Accuracy in parameter estimation (AIPE) -- 8.6.Estimating v -- 8.7.R code for Chapter 8 -- 8.8.Notes on SPSS syntax for Chapter 8 -- 8.9.Bibliography and further reading -- 9.Exploring messy data -- 9.1.Chapter overview -- 9.2.Statistical assumptions -- 9.3.Tools for detecting and assessing problems -- 9.4.Model checking in regression -- 9.5.R code for Chapter 9 -- 9.6.Notes on SPSS syntax for Chapter 9 -- 9.7.Bibliography and further reading -- 10.Dealing with messy data -- 10.1.Chapter overview -- 10.2.Dealing with violations of statistical assumptions -- 10.3.Robust methods -- 10.4.Transformations -- 10.5.R code for Chapter 10 -- 10.6.Notes on SPSS syntax for Chapter 10 -- 10.7.Bibliography and further reading -- 10.8.Online supplement 2: Dealing with missing data -- 11.Alternatives to classical statistical inference -- 11.1.Chapter overview -- 11.2.The null hypothesis significance testing controversy -- |
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Contents note continued: 11.3.Frequentist responses to the NHST controversy -- 11.4.Likelihood -- 11.5.Bayesian inference 11 -- 11.6.Information criteria -- 11.7.R code for Chapter 11 -- 11.8.Notes on SPSS syntax for Chapter 11 -- 11.9.Bibliography and further reading -- 11.10.Online supplement 3: Replication probabilities and prep -- 12.Multiple regression and the general linear model -- 12.1.Chapter overview -- 12.2.The multiple linear regression model -- 12.3.The impact of individual predictors on the model -- 12.4.Building a statistical model -- 12.5.R code for Chapter 12 -- 12.6.Notes on SPSS syntax for Chapter 12 -- 12.7.Bibliography and further reading -- 13.ANOVA and ANCOVA with independent measures -- 13.1.Chapter overview -- 13.2.ANOVA and ANCOVA as special cases of regression -- 13.3.One-way analysis of variance with independent measures -- 13.4.Exploring differences between level means -- 13.5.Analysis of covariance -- 13.6.ANOVA, ANCOVA and multiple regression -- |
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Contents note continued: 13.7.R code for Chapter 13 -- 13.8.Notes on SPSS syntax for Chapter 13 -- 13.9.Bibliography and further reading -- 14.Interactions -- 14.1.Chapter overview -- 14.2.Modeling interaction effects -- 14.3.Interactions in regression: moderated multiple regression -- 14.4.Polynomial regression -- 14.5.Factorial ANOVA -- 14.6.ANCOVA and homogeneity of covariance -- 14.7.Effect size in factorial ANOVA, ANCOVA and multiple regression -- 14.8.Statistical power to detect interactions -- 14.9.Problems with interactions in ANOVA and regression -- 14.10.R code for Chapter 14 -- 14.11.Notes on SPSS syntax for Chapter 14 -- 14.12.Bibliography and further reading -- 15.Contrasts -- 15.1.Chapter overview -- 15.2.Contrasts and the design matrix -- 15.3.Interaction contrasts -- 15.4.Post hoc contrasts and correction for multiple testing -- 15.5.Contrasts of adjusted means in ANCOVA -- 15.6.The role of contrasts in other statistical models -- 15.7.R code for Chapter 15 -- |
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Contents note continued: 15.8.Notes on SPSS syntax for Chapter 15 -- 15.9.Bibliography and further reading -- 16.Repeated measures ANOVA -- 16.1.Chapter overview -- 16.2.Modeling correlated or repeated measures -- 16.3.ANOVA with repeated measures -- 16.4.Combining independent and repeated measures: mixed ANOVA designs -- 16.5.Comparisons, contrasts and simple effects with repeated measures -- 16.6.MANOVA -- 16.7.ANCOVA with repeated measures -- 16.8.R code for Chapter 16 -- 16.9.Notes on SPSS syntax for Chapter 16 -- 16.10.Bibliography and further reading -- 17.Modeling discrete outcomes -- 17.1.Chapter overview -- 17.2.Modeling discrete outcomes in the general linear model -- 17.3.Generalized linear models -- 17.4.Logistic regression -- 17.5.Modeling count data -- 17.6.Modeling discrete outcomes with correlated measures -- 17.7.R code for Chapter 17 -- 17.8.Notes on SPSS syntax for Chapter 17 -- 17.9.Bibliography and further reading -- |
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Contents note continued: 17.10.Online supplement 4: Pseudo-R2 and related measures -- 17.11.Online supplement 5: Loglinear models -- 18.Multilevel models -- 18.1.Chapter overview -- 18.2.From repeated measures ANOVA to multilevel models -- 18.3.Multilevel regression models -- 18.4.Building up a multilevel model -- 18.5.Crossed versus nested random factors -- 18.6.Multilevel generalized linear models -- 18.7.R code for Chapter 18 -- 18.8.Notes on SPSS syntax for Chapter 18 -- 18.9.Bibliography and further reading |
| Summary |
Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data |
| Notes |
Formerly CIP. Uk |
| Bibliography |
Includes bibliographical references and indexes |
| Subject |
Psychology -- Statistical methods.
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Psychometrics.
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Social sciences -- Statistical methods.
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| LC no. |
2012012264 |
| ISBN |
0230577172 : |
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0230577180 : |
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9780230577176 : |
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9780230577183 : |
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