Briefly |
Create your statistic as a measure in the original collection. Then when you collect these measures (attributes) repeatedly, you build up a distribution of that statistic. |
To investigate a statistical measure using your Measures collection, define it as a measure in your original data collection. (How to make a new measure).
After you've defined the measure's name, be sure to give the measure a formula. Double-click in the Formula column to bring up the formula editor.
An example of a statistical measure
Let's look at an example. Suppose we've planted sunflowers in two garden plots, a sunny one and a shady one.
Your formulas will probably use what are called aggregate functions. Typical aggregate functions include mean( ) and median( ) and stddev( ).
If you're trying to figure out whether plants in the sun or the shade are taller, you have two attributes: whichPlot is categorical and height is continuous. You're probably interested in the difference of height between sunny and shady. In that case, your formula might be the difference in medians between the two garden plots:
median(height, whichPlot = "sunny") - median(height, whichPlot = "shady")
More about the formula editor.
Other uses of formulas: