1. Part III Taking Chances for Fun and Profit
Chapter 8   
Are Your Curves Normal? Probability and Why it Counts

2. Why Probability? Basis for the normal curve
Provides basis for understanding probability of a possible outcome
Basis for determining the degree of confidence that an outcome is “true”
Example:
Are changes in student scores due to a particular intervention that took place or by chance alone?

3. The Normal Curve (a.k.a. the Bell-Shaped Curve)
Visual representation of a distribution of scores
Three characteristics…
Mean, median, and mode are equal to one another
Perfectly symmetrical about the mean
Tails are asymptotic (get closer to horizontal axis but never touch)

4. The Normal Curve

5. Hey, That’s Not Normal!
In general, many events occur right in the middle of a distribution with few on each end.

6. More Normal Curve 101

7. More Normal Curve 101 For all normal distributions…
almost 100% of scores will fit between -3 and +3 standard deviations from the mean.
So…distributions can be compared
Between different points on the X-axis, a certain percentage of cases will occur.

8. What’s Under the Curve?

9. The z Score
A standard score that is the result of dividing the amount that a raw score differs from the mean of the distribution by the standard deviation of the distribution.
What do these symbols mean?

10. The z Score
Raw scores below the mean have negative z-scores
Raw scores above the mean have positive z- scores
A z score is the number of standard deviations from the mean
z scores across different distributions (with different means and std devs) are comparable

11. What z Scores Represent
The areas of the curve that are covered by different z scores also represent the probability of a certain score occurring.
So try this one…
In a distribution with a mean of 50 and a standard deviation of 10, what is the probability that a score will be 70 or above?

12. What z Scores Really Represent
Knowing the probability that a z score will occur can help you determine how likely it is that a factor other than chance produced the observed outcome.
Keep in mind… z scores are typically reserved for populations

13. Hypothesis Testing & z Scores
Any event can have a probability associated with it.
Probability values help determine how “likely” or “unlikely” the event might be
Range from 0 to 1
The key --- if something has less than 5% chance of occurring, we have a significant result

14. Using the Computer
Calculating z Scores