Relative percentage difference (RPD) is a way of measuring the variation in a set of data that looks at the variation as a proportion of the average or target value. For example, it may be used for quality or portion control in a factory that makes 1 kilogram (kg) and 10 kg bags of widgets. A 1 kg bag that was 100 g too light would have a greater RPD than a 10 kg bag that was 100 g too light; 10 and 1 percent respectively.

Determine what you are calculating RPD against. In the factory example, you would calculate the RPD against the stated weights of the widget bags, 1 kg or 10 kg. If you don't have a target, the most useful thing to calculate the RPD against would be the average value.

The RPD for a particular item in your data set is calculated like this: RPD = ((x - t)/t) * 100. Here, x is the value for the item -- say, your bag of widgets -- and t is the "target" value, either the actual target if there is one or just the average value. For example, for a bag of widgets that should weigh 1 kg, but in fact weighs 950 g: RPD = ((950g - 1000g)/1000g) * 100 = -5 percent.

From the resulting RPDs -- you can calculate an RPD for each item in the data set -- you can understand how large the variation is. In particular, if most of the widget bags have a very small RPD but a few have large RPDs, you would probably conclude the factory process is generally accurate, but sometimes significant mistakes are made.

#### Tip

RPD can be positive or negative, depending on the value relative to the target, so if you get a negative value, this does not mean you have done it wrong.

RPD is used in a similar way to relative standard deviation (RSD).

It is relatively easy to use a spreadsheet to automate the calculation of RPDs.