python z分数法

Z-score method is a statistical technique used to evaluate the relative position of a data point in a given data set. The z-score is the number of standard deviations that a data point is above or below the mean of the data set.

To calculate the z-score of a data point, we use the following formula:

z = (x - μ) / σ

where,
x = the data point
μ = the mean of the data set
σ = the standard deviation of the data set

For example, let's say we have a data set with the following values:

10, 12, 15, 18, 20

To find the z-score of the data point 18, we first need to calculate the mean and standard deviation of the data set.

Mean (μ) = (10 + 12 + 15 + 18 + 20) / 5 = 15
Standard deviation (σ) = 3.63

Now, we can calculate the z-score of the data point 18 using the formula:

z = (18 - 15) / 3.63 = 0.82

This means that the data point 18 is 0.82 standard deviations above the mean of the data set.

The z-score method is widely used in statistical analysis to identify outliers in data sets, to compare different data sets, and to evaluate the performance of models and algorithms.