# How to Specify Histogram Breaks in R

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How to Specify Histogram Breaks in R, you may want to specify the number of breaks or bins to use.

**How to Specify Histogram Breaks in R**

By default, the `hist()`

function uses Sturges’ Rule to determine the optimal number of bins based on the number of observations in the dataset.

However, you can override this default behavior by specifying the `breaks`

argument.

**Sturges’ Rule**

Sturges’ Rule is a formula that calculates the optimal number of bins to use in a histogram based on the number of observations in the dataset. The formula is:

Optimal Bins = ⌈log2n + 1⌉

where `n`

is the total number of observations in the dataset.

For example, if you have a dataset with 31 observations, Sturges’ Rule would suggest using 6 bins.

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**Specifying Breaks**

If you want to specify a different number of bins to use, you can use the `breaks`

argument in the `hist()`

function.

However, note that R will only use this as a suggestion and may choose to use a different number of bins if it deems it necessary.

To force R to use a specific number of bins, you can use the following code:

hist(data, breaks = seq(min(data), max(data), length.out = n+1))

Where `n`

is the desired number of bins.

**Example**

Suppose we have a dataset with 16 values:

data <- c(2, 3, 3, 3, 4, 4, 5, 6, 8, 10, 12, 14, 15, 18, 20, 21)

If we use the `hist()`

function without specifying any breaks, R will create a histogram with 5 bins:

hist(data)

However, if we try to specify 7 bins using the `breaks`

argument, R will only take this as a suggestion and may choose to use a different number of bins:

hist(data, breaks=7)

To force R to use 7 bins, we can use the following code:

hist(data, breaks = seq(min(data), max(data), length.out = 8))

This will create a histogram with 7 equally-spaced bins.

## Conclusion

While Sturges’ Rule is a useful default behavior for determining the optimal number of bins to use in a histogram, you may need to specify custom breaks depending on your specific dataset and visualization goals.

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