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front 1 Null hypothesis significance test | back 1 Procedures used to decide whether chance alone can account for apparent patterns in our data |

front 2 Null hypothesis | back 2 A statement embodying the idea that there is no pattern in the data or no difference between samples or no relationship between variables. (H |

front 3 Research hypothesis | back 3 An educated guess at the answer to a question about cause, mechanism, or function |

front 4 Statistical hypothesis | back 4 A hypothesis that states the specific relationships between variables and therefore parallels a prediction generated by a research hypothesis. |

front 5 Statistical alternative hypothesis | back 5 The reverse statement of the statistical null hypothesis. Stating that there is a pattern, or difference or relationship between the data sets. (H |

front 6 Critical significance level | back 6 This sets the decision point determining whether a null hypothesis is accepted or rejected. It is expressed as a probability. 5% is often used. (α) |

front 7 Degrees of freedom | back 7 One less than the sample size. |

front 8 Critical values | back 8 Values of statistics corresponding to a specific critical significance level and degrees of freedom. They can be looked up in a critical-value table. |

front 9 P-value / significance level | back 9 The probability of finding the observed, or more extreme, results
when the null hypothesis (H |

front 10 How do you decide to accept or reject the null hypothesis using the P-value? | back 10 Reject the null hypothesis if: P ≤ α Accept the null hypothesis if: P > α |

front 11 Type I error | back 11 Rejecting a true null hypothesis |

front 12 Type II error | back 12 Accepting a false null hypothesis |

front 13 Power of a (statistical) test | back 13 The probability of rejecting a false null hypothesis. Or the probability of not making an error. |

front 14 Parametric test | back 14 Null hypothesis significance testing techniques for which data must meet special criteria. The data must have a normal distribution - Use a t-Test |

front 15 Nonparametric test | back 15 Null hypothesis significance testing techniques that require fewer assumptions and do not rely on any distribution, normal or otherwise. - Use Chi-square |