## Statistical Methods for PsychologySTATISTICAL METHODS FOR PSYCHOLOGY surveys the statistical techniques commonly used in the behavioral and social sciences, especially psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasize conceptual understanding. Along with a significantly updated discussion of effect sizes and examples on how to write up the results of data analysis, this Sixth Edition continues to focus students on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version. |

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Excellent book on statictics - very clear, organized and readable.

#### Review: Statistical Methods For Psychology

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### Contents

Basic Concepts | 1 |

Describing and Exploring Data | 15 |

The Normal Distribution | 65 |

Sampling Distributions and Hypothesis Testing | 85 |

Basic Concepts of Probability | 111 |

Categorical Data and ChiSquare | 139 |

Hypothesis Tests Applied to Means | 179 |

Power | 225 |

Factorial Analysis of Variance | 413 |

RepeatedMeasures Designs | 461 |

Multiple Regression | 515 |

Analyses of Variance and Covariance as General Linear Models | 579 |

LogLinear Analysis | 629 |

Resampling and Nonparametric Approaches to Data | 659 |

Appendices | 691 |

725 | |

### Common terms and phrases

analysis of covariance analysis of variance approach assume assumption average behavior calculate cell Chapter chi-square column comparisons confidence limits consider contrasts correlation coefficient critical value data in Exercise data set degrees of freedom dependent variable discussed effect size equal equation error rate error term estimate example expected frequencies experimental fact factor familywise error rate Figure Gender hypothesis testing important independent interaction linear log-linear models LogPctSAT look main effects males mean squares measure median MSerror normal distribution null hypothesis obtained odds ratio participants plot population means predicted predictors probability problem procedure Q-Q plot random ranks regression coefficients relationship represents residual sample means sample sizes sampling distribution saturated model significant simple effects Source df SS SPSS SStotal standard deviation standard error statistic subjects summary table sums of squares SurvRate tion Total treatment Tukey Type I error