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Statistical Distributions with NumPy

Histograms, Part I

When we first look at a dataset, we want to be able to quickly understand certain things about it:

- Do some values occur more often than others?
- What is the range of the dataset (i.e., the min and the max values)?
- Are there a lot of outliers?

We can visualize this information using a chart called a *histogram*.

For instance, suppose that we have the following dataset:

d = [1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 4, 4, 4, 4, 5]

A simple histogram might show us how many 1’s, 2’s, 3’s, etc. we have in this dataset.

Value | Number of Samples |
---|---|

1 | 3 |

2 | 5 |

3 | 2 |

4 | 4 |

5 | 1 |

When graphed, our histogram would look like this:

### Instructions

**1.**

Look at the histogram to the right. How many values in the data set are equal to either 5 or 6?

Save the amount to the variable `value`

.