<prompt> Please answer with one of the option in the bracket. Write reasoning in between . Write answer in between .Q:You are reading through a recent article that reports significant decreases in all-cause mortality for patients with malignant melanoma following treatment with a novel biological infusion. Which of the following choices refers to the probability that a study will find a statistically significant difference when one truly does exist?? A: Type I error, B: Type II error, C: Power, D: Confidence interval, E: p-value,  <response>: This is asking about the definition of power in statistical testing. Power refers to the probability that a study will detect a true effect or relationship. The choices are various concepts in statistical testing:A Type I error - incorrect rejection of a true null hypothesis B Type II error - failure to reject a false null hypothesisC Power - probability of correctly rejecting the null hypothesis when the alternative hypothesis is trueD Confidence interval - range of values likely to contain the true effect sizeE p-value - probability of obtaining results at least as extreme as observed if the null hypothesis is trueC: Power 