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If 100 similar experiments were conducted, 5.2 of them would show similar results
5%
1/20
There is a 5.2% chance that A is more effective than B is due to chance
40%
8/20
There is a 94.8% chance that the difference observed reflects a real difference
15%
3/20
This is a statistically significant result
25%
5/20
Though A is more effective than B, there is a 5.2% chance the difference is due to a true effect
10%
2/20
Select Answer to see Preferred Response
This study has a p-value of 0.052 which suggests that there is a 5.2% chance that the difference between statin A and B is due to chance alone. To decide whether there is a real difference in a study, we ask, "what is the likelihood that we would have gotten this result just by random chance if the 2 interventions are the same (the null hypothesis)?". The answer to this question is known as the p-value, which is defined as the likelihood of getting this result or a more extreme result if the null hypothesis is true. The smaller this number, the less likely it is that the result was due to chance alone. Therefore, a p-value of 0.050 means that there is only a 5.00% chance that a significant difference would be seen even if the intervention is the same. Incorrect Answers: Answer 1: If 100 similar experiments were conducted, 5.2 of them would show similar results is incorrect and would suggest that the results of this study are a rare finding. Answer 3: There is a 94.8% chance that the difference observed reflects a real difference is not necessarily the correct way to interpret a p-value. Rather, a p-value of 0.05 means that there is a 5% chance that the difference is due to random chance alone. Answer 4: This is a statistically significant result is generally incorrect. Statistical significance depends on the cut-off value set by the researchers and/or statisticians. By convention, statistical significance is usually reached when the calculated p-value is less than 0.05. Answer 5: Though A is more effective than B, there is a 5.2% chance the difference is due to a true effect suggests that the results are due to random chance and there is a small (5.2%) chance that the difference is due to a real effect. Bullet Summary: The p-value represents the probability that the difference between 2 interventions is due to random chance alone.
3.6
(5)
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