Inverse distance weighting

Inverse Distance Weighting, often shortened to IDW, is a way of thinking about numbers. The farther away from someplace you get, the lower a number should be. This can be used to look at things like how much a person likes something, or how hot the temperature is, or how far away something is.

IDW works like this: let's say you wanted to figure out how much someone likes a game. To do that with inverse distance weighting, you would find out how far away from each other the people you asked about the game are. If someone is close to the game, then that person's opinion should count more than someone's opinion who is far away. So if the first person said they like the game a lot, and the second person said they really don't like the game, their opinions should be weighted differently. The person close to the game would count more than the person far away.

The same principle applies to other things like temperature or distance. So if you wanted to figure out what the temperature was around some place, you could look at the temperature around many different places in the area and weight each reading based on how close or far away it was. The readings that were close would weigh more than the readings that were far away.