1. Introduction to Hypothesis Testing
Chapter 4
Introduction to Hypothesis Testing
Part 2
Thurs. Sept. 5, 2013

2. One-Tailed and Two-Tailed Hypothesis Tests
Directional hypotheses – can you make a prediction about the direction of the effect?
One-tailed test – focus on either upper or lower tail of distribution
Ex?
Nondirectional hypotheses – cannot predict a direction of the effect
Two-tailed test – check both tails of the distribution

3. Determining Cutoff Points With Two-Tailed Tests
Divide up the significance between the two tails
For 1 tailed-test, if
using.05, all .05 is in
the relevant tail
For 2-tailed test, if
using .05, split betw
2 tails, so .05/2,
have .025 in each tail

4. 1- vs. 2-tailed tests
Given that a 1 tailed test has a larger rejection region,
The 1-tailed, directional, test is preferable.
If you have any idea of which direction your results may go, specify that in the Research Hyp.
Leads to better theory testing.
But…another viewpoint:

5. Notice the change in critical values:
For .05 significance level,
1-tailed test has 5% of scores in one tail  critical value is 1.64 (or if lower tail)
2-tailed test has 2.5% of scores in each tail  critical values are 1.96 and -1.96
How does this affect the rejection region?
Two-tailed test example:

6. Hypothesis Tests in Research Articles
Reported with regard to specific statistical procedures
(r = .78, p < .05)
Look for p < .05 or p < .01 or asterisks in tables (*) to indicate stat significance
“Near significant trend” if p < .10
Not significant, noted by ‘ns’

7. Hypothesis Tests in Research Articles
Shown as asterisks in a table of results
*Indicates that these results fell in the ‘rejection region’ and they differ significantly from the null hyp. (If no, asterisk  failed to reject the null)