After you collect all your financial data, you need to figure out what to do with it. You need to do some simple descriptive calculations of statistics and *probability, *which is the mathematics of uncertainty. In other words, you measure the likelihood of an event occurring using information about performance and relationships between variables.

When you have a lot of different values for a variable, finding an average will tell you what is the middle value — in other words, what is typical. Averages fall into different types, each with its own strengths and weaknesses, but in financial equations, the vast majority of averages will be the *mean average.*

To calculate the mean average, you need to add up all the values and divide that total by the number of values. In the example 1+2+3+4+5 = 15/5 = 3, the mean is 3.

To look at a *weighted average* (an average that takes into account differences in the importance of each value), attach a weight to each value. For instance, if one of the values in the preceding example was worth 60 percent of the entire sample and the rest weighted equally at 10 percent each, then the average changes a bit:

1(.1)+2(.1)+3(.1)+4(.1)+5(.6) = 0.1+0.2+0.3+0.4+3.0 = 4

The weighted average is 4 because the value 5 has more weight than the other values, bringing the average up a bit compared to the standard mean. The total weight is 100 percent, which is just 1 as a decimal, which is why each value is being multiplied by a decimal — .1 is 10 percent, .6 is 60 percent.

So whatever proportion a specific value consists of, multiple that by its decimal (for example, 75 percent would be .75).

Most people use the weighted average in situations where an investment portfolio has different proportions of investments or when accounting for time-weighted averages wherein more recent values are more important than historical ones.

Commonly used in financial analysis and projections are *moving averages,* which take the average from a predetermined number of days prior to a given day. So for a three-day moving average on Wednesday, you’d include data going back to Monday; for Thursday, you’d collect all the data going as far back as Tuesday; and for Friday, you’d go back to Wednesday.

This data helps illustrate whether the mean is increasing or decreasing over time.