## Applying Regression and Correlation: A Guide for Students and ResearchersThis book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach. The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable. Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe |

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### Contents

Preface | 1 |

MORE THAN ONE INDEPENDENT VARIABLE MULTIPLE | 27 |

CATEGORICAL INDEPENDENT VARIABLES | 40 |

I NEED TO DO REGRESSION ANALYSIS NEXT WEEK | 58 |

ISSUES IN REGRESSION ANALYSIS | 113 |

I NEED TO KNOW MORE OF THE THINGS THAT REGRESSION | 136 |

MODERATOR AND MEDIATOR ANALYSIS | 165 |

MULTILEVEL | 192 |

Equations | 216 |

Doing regression with SPSS | 228 |

Statistical tables | 237 |

245 | |

251 | |

### Other editions - View all

Applying Regression and Correlation: A Guide for Students and Researchers Jeremy Miles,Mark Shevlin No preview available - 2000 |

### Common terms and phrases

ANOVA assumption attend best fit books read calculate categorical variables causal Chapter coding Cohen collinearity constant correlation matrix covariance dataset dependent DfBeta DfFit dialog box equal error of slope examine example experimental grade graph group—l hassles histogram increase independent variable interaction effect intercept kurtosis latent variable lectures line of best linear regression LISREL logistic regression mean measure mediator multiple regression non-linear normal distribution number of books odds ratio outlier parameter estimates participants plot predicted value predictor variable problem psychological r-score regression analysis regression equation relationship represent residuals sample scale scattergraph scatterplot shown in Figure shown in Table shows significant slope coefficient slope Standardised slope SPSS standard deviation standard error Standardised slope beta statistical packages Std error stepwise regression Structural equation modelling technique transformation type I error unprimed variance vector zbooks zero