# Effect Size, Probability & Hypothesis testing

- Created by: kaytlhone101
- Created on: 02-05-18 18:34

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- Effect Size, Probability & Hypothesis testing
- Effect Size
- A general term for describing the thing we are interested in finding
- Cohen's D
- An effect size that expressed difference between two means in standard deviation units
- d = (M1 -M2)/?((SD12+SD22)/2)

- How
meaningful, impactful, influential is our effect
- Ranges on a numerical continuum; often has cut-offs for “small,” “medium,” and “large”

- Not affected by sample size

- Probability
- Probability distribution
- A curve describing an idealised frequency distribution of a particular variable from which you can get the probability

- Probability distribution
- Null Hypothesis Significance Testing
- an approach to evaluating our findings
- Experimental/ alternative hypothesis = effect.
- Evaluating the degree to which the data are incompatible with a model summarised by “the null hypothesis”

- alpha value
- the cut-off at which we decide whether we can reject the null hypothesis
- If p ?, then we typically cannot reject the null hypothesis

- Statistical
power
- the probability that we will reject the null hypothesis when it is appropriate to do so
- affected by sample size

- Type
I and Type II error
- Type I = False positive
- Type II = False negative

- Effect Size

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