## Statistics for the Social Sciences: A General Linear Model ApproachWritten by a quantitative psychologist, this textbook explains complex statistics in accessible language to undergraduates in all branches of the social sciences. Built around the central framework of the General Linear Model (GLM), Statistics for the Social Sciences teaches students how different statistical methods are interrelated to one another. With the GLM as a basis, students with varying levels of background are better equipped to interpret statistics and learn more advanced methods in their later courses. Russell Warne makes statistics relevant to students' varying majors by using fascinating real-life examples from the social sciences. Students who use this book will benefit from clear explanations, warnings against common erroneous beliefs about statistics, and the latest developments in the philosophy, reporting and practice of statistics in the social sciences. The textbook is packed with helpful pedagogical features including learning goals, guided practice and reflection questions. |

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Contents

1 Statistics and Models | 1 |

2 Levels of Data | 21 |

3 Visual Models | 35 |

4 Models of Central Tendency and Variability | 77 |

5 Linear Transformations and zScores | 103 |

6 Probability and the Central Limit Theorem | 127 |

7 Null Hypothesis Statistical Significance Testing and zTests | 151 |

8 OneSample tTests | 181 |

15 Applying Statistics to Research and Advanced Statistical Methods | 443 |

Appendix A1 zTable | 485 |

Appendix A2 tTable | 494 |

Appendix A3 FTable | 497 |

Appendix A4 Qtable Tukeys Post Hoc Test | 500 |

Appendix A5 Critical Values for r | 503 |

Appendix A6 2Table | 506 |

Glossary | 508 |

9 PairedSamples tTests | 215 |

10 Unpaired TwoSample tTests | 241 |

11 Analysis of Variance | 275 |

12 Correlation | 329 |

13 Regression | 369 |

14 ChiSquared Test | 403 |

Answer Key | 524 |

548 | |

564 | |

569 | |

### Other editions - View all

Statistics for the Social Sciences: A General Linear Model Approach Russell T. Warne Limited preview - 2017 |

### Common terms and phrases

alpha alternative hypothesis ANOVA Chapter chi-squared test column conduct correlation coefficient critical value dataset degrees of freedom dependent variable deviation scores difference effect size effect sizes example expected counts Formula group means histogram hypothesis statistical significance interpret interval labeled level of data linear transformation multiple regression NHST procedures nominal normal distribution null hypothesis null hypothesis statistical observed value odds ratio one-sample t-test one-tailed test outliers p-value paired-samples t-test Pearson’s population mean post hoc test predictions probability distribution regression line reject or retain reject the null rejection region relationship residuals retain the null sample mean sample members sampling distribution scatterplot shown in Figure shows Sidebar social sciences SPSS standard deviation statistical model statistical procedures statistical significance testing step tobs two-tailed test two-variable chi-squared test Type I error unpaired two-sample t-test variance video game visual model window z-observed z-scores