a. Click on the $1 coin to look at the figure which shows fortunes of 100 "very rich" people for a few seconds and write down your guess as to the average fortune in the following box. For example, the fortune of the person number 25 is $19.
| SCENARIO |
Results from polls and other statistical studies reported in a
newspaper or magazines often emphasize the point that the samples
were randomly selected. Why the emphasis on randomization? Couldn't
a good investigator do better by carefully choosing respondents
to a poll so that various interest groups were represented? Perhaps,
but samples selected without objective randomization tend to favor
one part of the population over another. For example, polls conducted
by sports writers tend to favor the opinions of sport fans. This
leaning toward one side of the issue is called sampling bias.
In the long run, random samples seem to do a good job of producing
samples that fairly represent the population. In other words,
randomization reduces sampling bias.
| QUESTION |
How do random samples compare to subjective samples in terms of
sampling bias?
| OBJECTIVES |
Subjective (or judgmental) samples will be compared to random
samples in terms of sampling bias. The goal is to learn why randomization
is an important part of data collection.
| ACTIVITY |
1. JUDGMENTAL SAMPLES
a. Click on the $1 coin to look at the
figure which shows
fortunes of 100 "very rich" people for a
few seconds and write down your guess as to the average fortune
in the following box. For example, the fortune of the
person number 25 is $19.