Random sampling is a way to remove bias in sample selection. For example, to pick a random sample of 20 people out of a population of a 1,000, you might put all 1,000 names in a hat, then draw 20 of them. Random sampling attempts to reduce bias in sample selection, since every member of the population has an equal chance of being selected. Note 5
Here are 60 circles. Can you select five circles that best represent the size of all the circles? (The average size of the five circles should equal the average size of all the circles).
Print this page.
Then look at the picture for no longer than 20 seconds. Mark the five circles you choose. Use the scale on the picture to measure the diameter of those five circles. Find the average diameter of your sample.
The average diameter of all 60 circles is 1 unit. How close to that is your sample?
(Note that a computer, selecting any five of the 60 circles randomly, might generate average diameters ranging from as small as 0.5 units to as large as 2.2 units.)