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

folding test | 1.61 | 0.4 | 2178 | 27 | 12 |

folding | 1.39 | 0.4 | 8234 | 100 | 7 |

test | 1.61 | 0.4 | 172 | 97 | 4 |

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

folding test | 0.44 | 0.3 | 8868 | 50 |

folding tester | 1.73 | 0.6 | 2681 | 22 |

folding text mac | 0.92 | 1 | 6251 | 28 |

folding textiles | 1.68 | 0.6 | 1740 | 63 |

folding trestle table | 1.19 | 0.8 | 2082 | 48 |

folding trestles | 1.74 | 0.8 | 8441 | 77 |

folding trestle legs | 1.66 | 0.5 | 5867 | 24 |

folding trestle table uk | 1.72 | 1 | 7769 | 4 |

folding trestle table legs | 1.59 | 0.6 | 6525 | 62 |

folding trestle table ireland | 1.43 | 0.6 | 3762 | 47 |

folding trestle table nz | 0.02 | 0.8 | 8919 | 12 |

folding trestle table bunnings | 0.44 | 0.4 | 2161 | 39 |

The difference between t-test and f-test can be drawn clearly on the following grounds: A univariate hypothesis test that is applied when the standard deviation is not known and the sample size is small is t-test. ... The t-test is based on T-statistic follows Student t-distribution, under the null hypothesis. ... The t-test is used to compare the means of two populations. ...

An F-test is any statistical test in which the test statistic has an F-distribution under the null hypothesis. It is most often used when comparing statistical models that have been fitted to a data set, in order to identify the model that best fits the population from which the data were sampled.