Menu location: **Data_Transforming and Deriving_Common Transforms_Z scores**.

Z scores, or standard scores, indicate how many standard deviations an observation is above or below the mean.

These scores are a useful way of putting data from different sources onto the same scale. For example, if you wanted to plot change over time in weight and blood pressure on the same graph you could transform the raw measurements into Z scores and plot them on the same scale.

The Z score reflects a standard normal deviate - the variation of across the standard normal distribution, which is a normal distribution with mean equal to zero and standard deviation equal to one.

If you assume that your data are drawn at random from a normal distribution you can use the sample based Z score: Z = (x-sample mean)/sample standard deviation.

__Example__:

Data A, become ---> | Z score: A |

1 | -1.3414 |

3 | -0.6415 |

5 | 0.0583 |

4 | -0.2916 |

7 | 0.7582 |

9 | 1.45803 |

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