Assume that 1100 births are randomly selected and exactly 556 of the births are girls. Use subjective judgment to determine whether the given outcome is unlikely, and also determine whether it is unusual in the sense that the result is far from what is typically expected.

The sample proportion for the births that are girls is 0.505. It is slightly higher than the expected value of 0.5, but the right way to answer if it is an unusual proportion is by performing an hypothesis test.

The hypothesis test results in not enough evidence to claim that the outcome is unlikely. This sample result has a probability of 0.7627 of appearing by pure chance in a population with proportion p=0.5.

Step-by-step explanation:

This is a hypothesis test for a proportion.

The claim is that the proportion of girls birth differs significantly from the expected proportion (50%).

Then, the null and alternative hypothesis are:

The significance level is 0.05.

The sample has a size n=1100.

The sample proportion is p=0.505.

p=X/n=556/1100=0.505

The standard error of the proportion is:

Then, we can calculate the z-statistic as:

This test is a two-tailed test, so the P-value for this test is calculated as:

As the P-value (0.7627) is greater than the significance level (0.05), the effect is  not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that the proportion of girls birth differs significantly from the expected proportion (50%).

mxb67

step-by-step explanation: