Select the method or formula of your choice.

Pearson's correlation is a measure of linear relationship between two variables, which ranges from +1 to -1. A correlation of +1 indicates a perfect positive linear relationship between variables.

The data are converted to ordinal data by taking the data values and coding as equally-spaced integers. For example, the series 4, 7, 20, is analyzed as 1, 2, 3, and thus, the series 4, 7, 7, 20, is analyzed as 1, 2, 2, 3.
###### Note

This is different from the Spearman statistic which analyzes the same sequence of 4, 7, 7, 20 as 1, 2.5, 2.5, 3.

Term | Description |
---|---|

n _{i+} | number of observations in the i^{th} row |

n _{+j} | number of observations in the j^{th} column |

n _{ij} | observations in the cell corresponding to the i^{th }row and j^{th} column |

n _{++} | total number of observations |

Spearman's rho is a measure of the linear relationship between two variables. Spearman's differs from Pearson's correlation only because the computations are done after the numbers are converted to ranks.

If i = 1, then:

If i = 2, 3,..., r, then:

If j = 1, then:

If j = 2, 3,..., c, then:

Term | Description |
---|---|

c | number of columns |

r | number of rows |

n _{i+} | number of observations in the i^{th} row |

n _{+j} | number of observations in the j^{th} column |

n _{ij} | observations in the cell corresponding to the i^{th} row and j^{th} column |

n _{++} | total number of observations |