You recently learned that a test statistic is used in hypothesis testing to help measure evidence against a null hypothesis. A test statistic allows us to take standard error into account when considering the evidence provided by a sample statistic. However, recall that the test statistic comes from one observed sample of data. Based on your knowledge of sampling distributions, you know that there are lots of different samples that could have been obtained. Each sample would have its own test statistic. In In-Class Activity 11.A, we learned that the evidence used in hypothesis testing is probability. The statistical evidence that we gather is always evidence in support of the alternative hypothesis and against the null hypothesis. We ask ourselves the question, "Do we have enough evidence to reject the null hypothesis?" According to a 2021 report published by the Federal Trade Commission (FTC], 29.4%% of claims to the FTC in 2020 were due to identity theft cases. ' Suppose that in the state of Florida, a random sample of 500 claims to the FTC are observed. Part A: Based on the published national percentage of 29.4%, about how many of the 500 Florida claims would you expect to be due to identity theft? Hint What is 20.4% of 500? Part B: What is the null hypothesis value of p? In your null hypothesis, round p to the nearest thousandth. Ho: Part C: In this example, we meet the following conditions for a one-sample z-test for proportions. Conditions for One-Sample Z-Test for Proportions 1. Large Counts: Check that np > 10 and n(1 - p) > 10. 2. Random Samples/Assignment: Check that the samples are random samples. 3. 10% Population Size: Check that the sample size, w, is less than 10%% of the population size, Non