- What is statistical power?
- Probability of rejecting false null hypothesis (1-β)
- 1-β error
- Probability of retaining true null hypothesis
- a and b
- Which of these is not a factor that affects power? (You should practice answering graphically and using an equation.)
- n (sample size)
- k (number of groups)
- σ (variations)
- α (type 1 error)
- Error Mean Square is based on mean of group variances
T/F
- In one way ANOVA, when the F value is substantially greater than 1 it means that there is a treatment effect or some sort of difference between the compared groups
T/F
- In an ideal world for any researcher you are testing the effects of one treatment on a group or organisms and there is no demonic intrusion or gradient effects of any kind, which statistical test would you use to ensure that you have the best power possible that will truthfully report any significant difference of these treatments? Hint: if there is no gradient effect (sunlight, moisture, etc) then you should probably avoid blocking your experimental design.
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