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Hypothesis Test of the Proportion of Girls in a gender selection experiment: A gender selection method claims that it can affect the probability of a baby being a girl, so that the probability becomes 3/4. Each student should simulate 20 births using this gender selection method. Using the TI-83 or 84 calculator, select MATH -> PRB, then type randInt(1,4, 20). This will randomly select 20 integers from 1 to 4. Let 1 = Boy and 2, 3, or 4 = Girl. This way, the probability of having a girl is 3/4. Next, construct a hypothesis test of the claim at the a = 0.10 significance level. Record the number of Girls born in your simulation: Rewrite the claim using statistical notation: Claim: Now write the opposite of this claim: Opposite: Construct the Null and Alternative Hypotheses. Ho: HI: Assuming the Null Hypothesis to be true, use your sample proportion to find the Test Statistic. Test Statistic: 1= Choose one of the following options: Option 1, Traditional Method: Option 2, P-value Method: Critical Value(s): 1 = P-value = Circle one of the following initial conclusions, based on the option chosen above: Reject Ho Fail to Reject Ho Turn Over ->Based on your conclusion about the Null Hypothesis, write a final conclusion which addresses the original claim: We designed our simulation to sample from a set that truly does have a proportion equal to 3/4. However, due to sampling variability, there may have been some tests that warranted rejection of the original claim. Since our significance level was a = 0.10, this means that 10% of all such tests will reject the null hypothesis when it is actually true. What percentage of students' tests warranted rejection of the original claim? Was this percentage close to 10%