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Null hypothesis significance testing
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Null hypothesis significance testing
Parameters show effects/what we are looking for
- I.e relationship between variables or difference between means
- all parameters have a related distribution
- For any parameter (b value) we can work out probability of getting outcome if null hypothesis is true
sample size can affect significance, bigger sample creates more significance
effect size
- Standardise parameter = B = r
- 0.1 = small. 0.5 = large
- Cohen's d = standardised difference between 2 means
- Standardise parameter = B = r
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- Mind Map on Null hypothesis significance testing, created by Kayla Campbell on 05/10/2017.
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- Kayla Campbell
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