# When a histogram has a longer tail to the right it is said to be

## What is a Histogram?

A histogram is a graphical representation of the distribution of numerical data. It is an accurate representation of the distribution of numerical data. It is a graphical representation of the distribution of numerical data.

## What is a Long Tail?

In statistics, a long tail is simply a distribution where most of the values are clustered around the centre, but there is a small (or very small) number of values that are much higher or lower than the rest. For example, consider the following two histograms:

## What is a Right-Skewed Histogram?

A right-skewed histogram is a type of histogram that is skewed to the right. This means that the bulk of the data is concentrated on the left side of the histogram, and there is a long tail on the right side.

Right-skewed histograms are often used to represent data that is not symmetrical. For example, data that is skewed to the right may have a few outliers on the left side, but most of the data will be clustered on the right side.

A right-skewed histogram can be created by adding more data points to the right side of the distribution than to the left side. This will create a long tail on the right side of the histogram.

## How to Tell if a Histogram is Right-Skewed

A right-skewed histogram will have a longer tail on the right side of the distribution. This means that the majority of the data will be clustered on the left side of the histogram, with fewer data points on the right side. The right side of the histogram might also be flat, while the left side has a more mound-shaped curve.

## Examples of Right-Skewed Histograms

A right-skewed histogram will have a longer tail on the right side of the histogram. This indicates that there are more values in the dataset that are greater than the mode. The mode will still be the highest value on the histogram, but there will be more values to the right of it. Right-skewed histograms are also sometimes called positively-skewed histograms.

Some examples of data that might produce a right-skewed histogram include:
-Amount of money people spend on lunch every day
-The amount of time people spend on social media every day
-The length of time people spend commuting to work every day