Returns the number of histogram bins using a given method.

## Syntax

**HISTBINS**(**X**, **Method**)

- X
- is the input data series (one/two-dimensional array of cells (e.g., rows or columns)).
- Method
- is a switch to select the calculation method (1 = Sturges's formula, 2 = Square-root, 3 = Scott's Choice, 4 = Freedman-Diaconis choice, 5 = Optimal (default)).
Method Description 1 Sturges's Formula. 2 Square-root Choice. 3 Scott's Choice. 4 Freedman-Diaconis choice. 5 Optimal (Loss-Function min) (default).

## Remarks

- The input data series may include missing values (e.g., #N/A, #VALUE!, #NUM!, empty cell), but they will not be included in the calculations.
- The number of bins, $k$, can be assigned directly or calculated from a suggested bin width $h$.
- $k$ is defined in terms of $h$ as follows: $$k=\left \lceil \frac{\mathrm{max}(X)-\mathrm{min}(x)}{h} \right \rceil$$ Where:
- $h$ is the input data series.

- Sturges's formula for the number of bins, $k$, is: $$k = \lceil \log_2 n + 1 \rceil$$ Where:
- $n$ is the number of non-missing values in the input time series data.

- Implicitly bases the number of bins on the range.
- And can perform poorly for $n \lt 30$.

- The square-root choice for the number of bins, $k$, is: $$k = \sqrt{n}$$ Where:
- $n$ is the number of non-missing values in the input time series data.

- Scott's choice for the bin
*width*, $h$, is: $$h = \frac{3.5 \sigma}{n^{\frac{1}{3}}}$$ Where:- $\sigma$ is the standard deviation of the input data series.
- $n$ is the number of non-missing values in the input time series data.

- The Freedman–Diaconis choice for the bin width, $h$, is: $$h = 2 \dfrac{\operatorname{IQR}(X)}{{\sqrt[3]{n}}}$$ Where:
- IQR is the interquartile range of the input data series.
- $X$ is the input data series.
- $n$ is the number of non-missing values in the input time series data.

## Files Examples

## Related Links

## References

- Balakrishnan, N., Exponential Distribution: Theory, Methods and Applications, CRC, P 18 1996.

## Comments

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