# Mean as the balancing point

Explore how we can think of the mean as the balancing point of a data distribution.

You know how to find the mean by adding up and dividing. In this article, we'll think about the mean as the balancing point. Let's get started!

## Part 1: Find the mean

Interesting! In the first two problems, the data was "balanced" around the number six.

**Try the next one without finding the total or dividing. Instead, think about how the numbers are balanced around the mean.**Notice how the and were "balanced" on either side of the :

Can you see how the data points are always balanced around the mean? Let's try one more!

## Part 2: A new way of thinking about the mean

You might have noticed in Part 1 that it's possible to find the mean without finding the total or dividing for some simple data sets.

**Key idea:**We can think of the mean as

**the balancing point**, which is a fancy way of saying that the total distance from the mean to the data points below the mean is equal to the total distance from the mean to the data points above the mean.

### Example

In Part 1, you found the mean of to be . We can see that the total distance from the mean to the data points below the mean is equal to the total distance from the mean to the data points above the mean because :

#### Reflection questions

## Part 3: Is the mean always the balancing point?

Yes! It is always true that the total distance below the mean is equal to the total distance above the mean. It just happens to be easier to see in some data sets than others.

For example let's consider the data set .

Here's how we can calculate the mean:

And we can see that the total distance below the mean is equal to the total distance above the mean because :

## Part 4: Practice

## Challenge problem

The mean of four data points is . Three of the four data points and the mean are shown in the diagram below.