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In the study of statistics, a statistically significant result (or one with statistical significance) in a hypothesis test is achieved when the p-value is less than the defined significance level.The p-value is the probability of obtaining a test statistic or sample result as extreme as or more extreme than the one observed in the study whereas the significance level or alpha tells a researcher how extreme results must be in order to reject the null hypothesis.While rejecting the null hypothesis is a central goal in most scientific study, it is important to note that the rejection of the null hypothesis is not equivalent to the proof of the researcher’s alternative hypothesis.
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The needed effect is much smaller since this experiment requires much 'power'.
The sample size depends on the confidence interval and confidence level.
This is to be expected because larger the sample size, the more accurately it is expected to mirror the behavior of the whole group.