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Useful For |

Code Book |
Reports | Provides a quick look at all your variables at once. The level of measurement automatically controls which summary statistics are displayed. |

Frequencies |
Descriptives | Tells you how many of each category value you have. Most useful for categorical variables because you can run all of them at once. |

Descriptives |
Descriptives | Gets basic scale variable information, such as the mean and standard deviation. |

Explore |
Descriptives | Based on a famous book, Exploratory Data Analysis, looks at all kinds of variables as well as pairs of variables. |

Crosstabs |
Descriptives | Tests to see if categorical variables are independent of each other or related to each other. |

Means |
Compare Means | Calculates subgroup means and related statistics for dependent variables within categories of one or more independent variables. |

One-Sample T-Test |
Compare Means | Tests whether the mean of a single variable differs from a specified value (for example, a group using a new learning method compared to the school average). |

Independent Samples T-Test |
Compare Means | Tests whether the means for two groups differ on a continuous dependent variable (for example, females versus males on income). |

Paired Samples T-Test |
Compare Means | Tests whether a significant difference exists in the mean under two conditions (for example, before versus after, or standing versus sitting). |

One-Way ANOVA |
Compare Means | Tests whether the means for two or more groups differ on a continuous dependent variable (for example, drug1 versus drug2 versus drug3 on depression). |

Bivariate Correlation |
Correlate | Determines the similarity in the way two continuous variables change in value from one case (row) to another through the data. |

Linear Regression |
Regression | Predicts a continuous dependent variable from one or more continuous independent variables |

One Sample |
Nonparametric Tests | Compares the distribution of a categorical dependent variable to population norms. |

Independent Samples |
Nonparametric Tests | Tests whether the means or medians for two or more different groups differ on a dependent variable. |

Related Samples |
Nonparametric Tests | Tests whether the means or medians of the same group differ under two conditions or time points. |

Univariate |
General Linear Model | An extension of one-way ANOVA in which there is more than one independent variable. |

Multivariate |
General Linear Model | An extension of one-way ANOVA in which there is more than one dependent variable. |

Repeated Measures |
General Linear Model | An extension of the paired-samples t-test in which the same group is assessed under two or more conditions or time points. |

Binary Logistic |
Regression | Used in situations similar to linear regression but the dependent variable is dichotomous. |

Multinomial Logistic |
Regression | An extension of binary logistic regression in which the dependent variable is not restricted to two categories. |

Discriminant |
Classify | Builds a predictive model for group membership based on the linear combinations of predictors that best separate the groups. |