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

identifying outliers calculator worksheets | 0.85 | 0.6 | 3230 | 31 | 42 |

identifying | 0.09 | 0.9 | 4041 | 88 | 11 |

outliers | 0.35 | 0.7 | 7705 | 39 | 8 |

calculator | 0.77 | 0.9 | 4328 | 1 | 10 |

worksheets | 0.64 | 0.1 | 1284 | 79 | 10 |

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

identifying outliers calculator worksheets | 0.76 | 1 | 9203 | 60 |

Outlier. To determine if there are outliers we must consider the numbers that are 1.5·IQR or 10.5 beyond the quartiles. first quartile – 1.5·IQR = 3.5 – 10.5 = –7 third quartile + 1.5·IQR = 10.5 + 10.5 = 21 Since none of the data are outside the interval from –7 to 21, there are no outliers.

The first step in identifying outliers is to pinpoint the statistical center of the range. To do this pinpointing, you start by finding the 1st and 3rd quartiles. A quartile is a statistical division of a data set into four equal groups, with each group making up 25 percent of the data.

An outlier is a number in a set of data that is very far from the rest of the numbers. There is no real way to find an outlier.

There is no formula for finding an outlier if, by formula, you mean some statistical or mathematical method. Outliers are points that are surprising. Surprise is a characteristic reaction of humans (and other animals) not of formulas. Surprise is good.