Out of your n = 50 confidence intervals, 44 of them correctly contained y So the sample proportion of confidence intervals which correctly captured the population mean salary is $= 0.88 44/50= 0.88 Conduct a hypothesis test for the following claims, using a 5% level of significance: 0 =0.05 Ho: p = 0.90; the true proportion, p. of 90% confidence intervals which contain g is equal to 0.90. Ha: P # 0.90; the true proportion, p, of 90% confidence intervals which contain g is NOT equal to 0.90. State and interpret the results of your hypothesis test. Include a p-value with your answer What type of error (type 1/ type 2) ray have been made? Explain what it would mean if it did occur. If H, is true, what proportion of hypothesis tests will produce a type 1 error? That is, what percent of all possible sample proportions (p's) will lie in the rejection region