> For the complete documentation index, see [llms.txt](https://ai.nuhil.net/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ai.nuhil.net/statistics/types-of-measure.md).

# Types of Measure

**Central Tendency** tells you about the centers of the data. Useful measures include the mean (Weighted Mean, Harmonic Mean, Geometrical Mean), median, and mode (Mode, Multimode). 

* **Harmonic Mean** is the reciprocal of the arithmetic mean of the reciprocals.\
  $$\frac{n}{\sum\_i^n(\frac{1}{x{i}})}$$ ,  where $$i=1,2,...n$$ and $$n$$ is the number of items in the dataset $$x$$ . 
* **Geometric Mean** is the `n-th` root of the product of all $$n$$ elements $$x\_i$$ *in a dataset* $$x$$*.*\
  $$\sqrt\[n]{\prod\_i^n x\_{i}}$$ , where $$i=1,2,...n$$ and $$n$$ is the number of items in the dataset $$x$$ .

**Variability** tells you about the spread of the data. Useful measures include variance, Standard deviation, Skewness, Percentile, and Range.

**Correlation or Joint Variability** tells you about the relation between a pair of variables in a dataset. Useful measures include covariance and the correlation coefficient.


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