1. Graphs and Chi Square

2. Collecting Data
Set up a data table with the first heading on the left reflecting the independent variable.
Examples:

3. Collecting Data
Next, record the dependent variables to the right of the independent variable.

4. Graphs
Types of graphs:
Key = LABEL!

5. Chi Square (X ) 2
Purpose: to determine the statistical difference between what is expected and what is observed.
Start with a “null hypothesis.” This states that you expect there to be no difference, something will not be present, or have no effect.
In other words, you think the expected and observed will be the same. (differ only by chance)

6. Chi Square (X ) 2
Once you calculate Chi Square, determine the “p value.” (calculated probability)
Determine whether to accept or reject the null hypothesis.
If p is less than 0.05, REJECT null hypothesis.
0.05 is the “critical value” (< or = 0.05 is statistically significant… differences between observed and expected are unlikely to have occurred by chance)
Goodness of fit statement: “Since p is more/less than 0.05, we accept/reject the null Hypothesis (Ho) that...”

7. Now for some fun!