## Statistical Methods for PsychologySTATISTICAL METHODS FOR PSYCHOLOGY surveys the statistical techniques commonly used in the behavioral and social sciences, especially psychology and education. This book has two underlying themes that are more or less independent of the statistical hypothesis tests that are the main content of the book. The first theme is the importance of looking at the data before formulating a hypothesis. With this in mind, the author discusses, in detail, plotting data, looking for outliers, and checking assumptions (Graphical displays are used extensively). The second theme is the importance of the relationship between the statistical test to be employed and the theoretical questions being posed by the experiment. To emphasize this relationship, the author uses real examples to help the student understand the purpose behind the experiment and the predictions made by the theory. Although this book is designed for students at the intermediate level or above, it does not assume that students have had either a previous course in statistics or a course in math beyond high-school algebra. |

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#### Review: Statistical Methods for Psychology

User Review - Brent - GoodreadsBest statistics textbook out there. Very accessible in terms of formulations and the logic behind them. And, yes, I was nerdy enough to read it cover to cover Read full review

#### Review: Statistical Methods for Psychology

User Review - GoodreadsBest statistics textbook out there. Very accessible in terms of formulations and the logic behind them. And, yes, I was nerdy enough to read it cover to cover Read full review

### Contents

Describing and Exploring Data | 16 |

The Normal Distribution | 73 |

Sampling Distributions and Hypothesis Testing | 91 |

Copyright | |

20 other sections not shown

### Common terms and phrases

analysis of variance Appendix assume assumption average binomial binomial distribution boxplot calculate cell Chapter column comparisons confidence limits consider critical value data in Exercise data set defined degrees of freedom dependent variable difference scores discussed equal equation error rate error term estimate example Exhibit expected frequencies experimental fact familywise error rate Figure formula gender given important independent interaction linear log-linear models look main effects males measure median Minitab MSerror multiple normal distribution null hypothesis observations obtained parameter plot predicted predictors probability procedure random ratio reason regression coefficients reject H0 relationship represent sample mean sample sizes sample statistics sample variance sampling distribution scale shown significant simple effects skewed Source df SS SPSS standard deviation standard error statistics stem-and-leaf display subjects summary table sums of squares SurvRate tion Total treatment trials true two-tailed test Type I error