Hypothesis testing:
Five steps for hypothesis testing:
1.
2.
3.
4.
Samples
M
SD2
SD
Populations
Random selection:
Convenience or haphazard selection:
Random assignment:
A first example:
A doctor gives a patient a new type of anti-depressant. Is there any
improvement compared to a larger population of depressed population?
Assume that depression scores follow a "normal curve"
(Population) M = 69.5
SD = 14.1
X = 41
1. Convert research questions to statistical hypotheses.
2. What are the characteristics of our comparison distribution?
Why can we use the normal curve?
Not all distributions are normal.
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3. Determine "cut-off" scores.
Conventional level of statistical significance
One tailed vs. two tailed
4. Determine your observation or sample score.
Convert observation to Z score.
5. Accept or reject the NULL hypothesis.
How would we write it down?
A second example:
Is memory affected by stress? Ask 25 people to give a talk and then
remember a set of photographs.
Mean recall = 48, SD=7, General population mean=53
Shift to a sample of observations from a single observation.
3 key characteristics of a distribution of means.
1.
2.
3.
So how do we correct the problem?
Formulas: