Section 32 Types of variable

Above, I have briefly explained why I have chosen variables as the best candidate for the nodes in our causal maps.

So here are a few points about variables.

We will need to distinguish different types of variable. Here are a few key types:

• ◪ continuous, limited variables like percentage, usually specified as going from zero (“nothing”) to 1 (“everything”). I call them “[lo-hi variables][#lo-hi]” but I would love to hear of a better name. Can also be expressed as a %, because this is more familiar to people. Our interpretation of these numbers is very loose, they might be proportions or probabilities or numbers expressing membership of a fuzzy set Zadeh (1973), Ragin (2008).
• ◨ false/true variables like “the project is implemented (yes or no)”
• ◢ continuous, unlimited variables like height, income
• ..… and various others, see xx.

When actually coding causal maps, we will mostly use lo/hi ◪ variables, as false/true ◨ variables are a special case of them, with just the levels 0 (no) and 1 (yes).