Education.com
Try
Brainzy
Try
Plus

# Putting Story Structure to Work (page 3)

By John Wiley & Sons, Inc.
Updated on Jan 14, 2011

The logic for getting around this problem is the same as it was for the coin-flip example. For the coin flip, we judged one hundred heads in a row as a highly improbable event assuming that the coin was fair. The odds of a fair coin coming up heads one hundred times in a row are very small. So if we observe that event—one hundred heads in a row—we conclude that our assumption must have been wrong. It's not a fair coin. So the saw-the-ad group being higher than the other group may also not be improbable—but what if that group was much more likely to answer yes? Just as we judged that there was something funny about the coin, so too we should judge that there is something funny about people who have seen the ad—at least funny when it comes to answering our question.

Of course funny in this context means "improbable." In the case of the coin, we knew how to calculate the "funniness," or improbability, of events because we knew the number of possible outcomes (two) and the probability of each individual outcome (.5), so it was easy to calculate the odds of successive events, as shown in Table 1. But here's our next problem: How do we calculate the "funniness," or probability, of other types of events? How much worse does the vocabulary of kids who watched videos have to be compared to that of kids who didn't watch videos before we're prompted to say, "Hey, these two groups of kids are not equal. If they were equal, their vocabularies would be equal. But their vocabularies are very unequal."

All of this description of coins, advertisements, and experiments is really a prelude to the lesson. I'm trying to get students to understand and care about the goal of the lesson, which is to explain how we can determine the probability of an event occurring by chance. That is the conflict for this lesson. Our worthy adversary in pursuit of this goal is not Darth Vader but the fact that most events we care about are not like coin flips—they don't have a limited number of outcomes (heads or tails) for which we know the probabilities (50 percent). That's a complication, which we address with a particular type of graph called a histogram; but implementing this approach leads to a further complication: we need to calculate the area under the curve of the histogram, which is a complex computation. The problem is solved by the Z-score, which is the point of the lesson (Figure 12).

View Full Article
Add your own comment