1.1 Mean
The first measure we will discuss is very likely one you have heard of before: the mean, also known as the average. Consider the below sample of \(n=5\) countries and their associated income per person (GDP per capita, PPP$ inflation-adjusted).
Country | Income per person ($) |
---|---|
Chad | 1740 |
Lao | 6940 |
Turkey | 25000 |
Mozambique | 1170 |
Norway | 66300 |
We can calculate the mean of these values simply by adding them up, and then dividing by the number of values, \(n = 5\): \[\begin{align} \text{mean income per person} &= (1740 + 6940 + 25000 + 1170 + 66300) \div 5 \\ &= 101150 \div 5 \\ &= 20230 \end{align}\]
Let's now introduce a little bit more notation. If we denote any one of these income values to be \(x_i\), where \(i\) can take any value from \(1\) to \(n = 5\), that means we can denote each value as follows:
- \(x_1 = 1740\)
- \(x_2 = 6940\)
- \(x_3 = 25000\)
- \(x_4 = 1170\)
- \(x_5 = 66300\)
The mean of a sample such as this, the sample mean, is usually denoted \(\overline{x}\), pronounced "x bar". Using this notation, we can succinctly define the sample mean to be:
\[\begin{align} \overline{x} = \dfrac{1}{n} \sum_{i=1}^{n} x_i. \end{align}\]
Note that \(\sum\) is a summation sign, so that if we read out \(\displaystyle \sum_{i=1}^{n}\) in words, we would say, "the sum from \(i=1\) to \(n\)". In other words, this formula is telling us to add up the values \(x_1\) up to \(x_n\), and then divide that sum by \(n\). Remembering that we had \(n=5\) in our example, hopefully you can see that is exactly what we have done when calculating the sample mean of \(20230\) above.
As mentioned, the sample mean is usually denoted \(\overline{x}\). The population mean is usually denoted \(\mu\). Usually, we do not know what the true value of \(\mu\) is, but we can use the sample mean, \(\overline{x}\), to try and estimate it.
Your turn: Consider the following five values:
\[7770, 10200, 954, 1640, 23000. \]
What is the mean of these values?
8712.8