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If the data is distributed somewhat evenly around the mean, the bars on each side of the middle bar will have roughly the same height. This is called a symmetric distribution.

In a symmetric histogram, the mean is typically found in the tallest bar.

When the data is not evenly distributed around the mean the histogram becomes skewed.

For skewed histograms, the mean is usually **not** found in the tallest bar.

Based on the distribution of a data set, different types of statistics are more suitable than others.
### Theory

## Symmetric distribution

For a symmetric distribution, all values are spread out somewhat evenly around the center. Since both the mean and standard deviation take into account the **actual values of all data points**, these statistics are usually more suitable when describing this distribution.
### Theory

## Skewed distribution

When a distribution is skewed, there can be outliers. A small number of extreme values unevenly distributed can affect both the mean and standard deviation significantly, leading to a misrepresentation of the data set. Since the median and IQR don't take into account the actual values of all points, but rather the **number of data points**, these statistics are usually preferable for skewed distributions. Any outliers do not affect these statistics.

Two ketchup companies investigate the weight of their 64-ounce bottles. Below are the results for both companies.

Analyze the results for both companies and determine which statistics are more suitable.

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