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

purpose of anova analysis | 0.55 | 0.4 | 5364 | 68 | 25 |

purpose | 0.3 | 1 | 1081 | 84 | 7 |

of | 0.64 | 0.2 | 1774 | 12 | 2 |

anova | 0.77 | 1 | 1991 | 88 | 5 |

analysis | 1.05 | 0.8 | 7837 | 67 | 8 |

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

purpose of anova analysis | 0.79 | 0.8 | 3250 | 15 |

The real advantage of using ANOVA over a t-test is the fact that it allows you analyse two or more samples or treatments (Creighton, 2007). A t-test is appropriate if you have just one or two samples, but not more than two. The use of ANOVA allows researchers to compare many variables with much more flexibility.

A one-way ANOVA is used when you have one independent variable with multiple conditions. For example, you would use a one-way ANOVA if you wanted to determine the effects of different types of fertilizer on the number of fruits your lemon tree produces. Your independent variable is the fertilizer type.