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Type I error ‐ False Positive
•  is probability of statistically significant result when null hypothesis is true i.e. there is no difference
• 0.5 or 5% = 1 in 20 chance of incorrectly rejecting null hypothesis
Type II error ‐ False negative
•  is the probability of a non-significant result when null hypothesis is not true
• 1-  is the power of the study to detect a difference of a given size
• Typically 80 or 90% i.e. 1 in 5 or 1 in 10 chance of falsely rejecting null hypothesis
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PRECONGRESS COURSE 13 I BARCELONA, SPAIN – 1 JULY 2018 17