Data Session 9, Part B: Selecting the Sample

Session 9, Part B:
Selecting the Sample (30 minutes)

In This Part: Fair Sampling | A Fair Sampling Method | Variation in Estimates

You may have noticed that your estimates for the total penguin population vary quite a bit based on both the sample size and which sub-regions were sampled. The decision about how to select a sample, accordingly, is a critical one in statistics. It is important that each part of the population be treated fairly. If you are fair in the selection, then you should obtain a representative sample and thus a more fair estimation procedure. In earlier sessions, you looked at notions of fairness and randomness and noticed that people have a difficult time being fair or random. So what methods can you use to accomplish fair sampling? Note 4


Problem B1
How might you select 10 sub-regions from the 100 total sub-regions so that you would be most likely to have a "representative" sample for estimating the size of the penguin population in the entire region? You can use the empty chart below to explore your ideas.

To select 10 sub-regions from the 100 total sub-regions in a "fair" way requires that each of the 100 sub-regions has the same chance of being selected. You can accomplish this with random selection. How might you select 10 sub-regions in a random fashion? Close Tip

Video Segment
In this video segment, groups of participants devise methods for collecting a random sample of penguins. Watch this segment after you have completed Problem B1 and compare your method with that of the onscreen participants. Do these methods ensure that the samples will be random?

If you're using a VCR, you can find this segment on the session video approximately 6 minutes and 26 seconds after the Annenberg Media logo.

Next > Part B (Continued): A Fair Sampling Method

Session 9: Index | Notes | Solutions | Video