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A researcher studying extrasensory perception (ESP) tests 300 students. Each student is asked to predict the outcome of a large number of coin flips. For each student, a hypothesis test using a \(5 \%\) significance level is performed. If the \(\mathrm{p}\) -value is less than or equal to \(0.05\), the researcher concludes that the student has ESP. Assuming that none of the 300 students actually have ESP, about how many would you expect the researcher to conclude do have ESP? Explain.

Short Answer

Expert verified
The researcher would incorrectly conclude that approximately 15 students out of 300 have ESP, due to the 5% significance level used in the hypothesis test.

Step by step solution

01

Understand the significance level

The significance level, also denoted as alpha \(\alpha\), is the probability of rejecting the null hypothesis when it is true. In this case, the null hypothesis is that the student does not have ESP. The significance level is set at 0.05, which means there is a 5% chance of falsely rejecting the null hypothesis.
02

Apply the significance level to the number of tests

The researcher is testing 300 students. If the null hypothesis is true for all students then, on average, we expect about 5% of them to still produce a p-value less than 0.05 purely by chance.
03

Calculate the expected number of false positives

To find out how many students we'd expect to incorrectly identify as having ESP, we multiply the total number of students by the probability of a false positive. So, the expected number of false positives is \(300 * 0.05 = 15\) students.

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