Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|

stats alpha | 0.55 | 1 | 2248 | 20 | 11 |

stats | 0.24 | 1 | 144 | 13 | 5 |

alpha | 1.91 | 0.1 | 6893 | 6 | 5 |

Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|

stats alpha | 1.77 | 0.7 | 7919 | 12 |

stats alpha level | 0.7 | 0.2 | 8900 | 58 |

stats alpha and beta | 1.77 | 0.8 | 2698 | 29 |

stats alpha beta error | 0.83 | 0.7 | 3809 | 38 |

alpha level stats definition | 0.58 | 0.3 | 3680 | 7 |

ap stats alpha level | 1.25 | 1 | 6998 | 60 |

Alpha levels are related to confidence levels: to find alpha, just subtract the confidence interval from 100%. for example, the alpha level for a 90% confidence level is 100% – 90% – 10%. To find alpha/2, divide the alpha level by 2.

Recall that if the p-value is less than alpha in a one-tailed test, this means that the observed statistic lies in the rejection region. The name "rejection" refers to the rejection of the null hypothesis. So if the p-value is less than alpha in a one-tailed test, then the null hypothesis should be rejected. So the answer is C)

Alpha, the significance level, is the probability that you will make the mistake of rejecting the null hypothesis when in fact it is true. The p-value measures the probability of getting a more extreme value than the one you got from the experiment. If the p-value is greater than alpha, you accept the null hypothesis.