In the Data Analysis portion of the article the authors report that they completed a power analysis to determine the power of their study with the sample size utilized. They report a power of 90%. What does this mean

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Step-by-step explanation:

The power of a test simply gives the probability of Rejecting the Null hypothesis, H0 in a statistical analysis given that the the alternative hypothesis, H1 for the study is true. Hence, the power of a test can be referred to as the probability of a true positive outcome in an experiment.

Using this definition, a power of 90% simply means that ; there is a 90% probability that the a Pvalue less Than the α - value of an experiment is obtained if there is truly a significant difference. Hence, a 90% chance of Rejecting the Null hypothesis if truly the alternative hypothesis is true.

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step-by-step explanation:

96 39 cause 135 -96=39 im smart (i used a calculater)