The testable hypotheses in this situation are Ho :µ = 14 vs. Ha : µ > 14 1. Identify the consequences of making a Type l error. OA. The company does not charge the customer the premium rate when they should. OB. The company charges the customer the premium rate when they should not. OC. The company charges the customer the premium rate when they should. OD. The company does not charge the customer the premium rate when they should not. 2. Identify the consequences of making a Type Il error. OA. The company charges the customer the premium rate when they should not. OB. The company does not charge the customer the premium rate when they should. OC. The company does not charge the customer the premium rate when they should not. OD. The company charges the customer the premium rate when they should. To monitor the billing rate, the manager is going to take a random sample of 20 surveys each shift and calculate the average survey time in the sample. They make a decision rule that if x > 14.5, they will charge the premium rate for that shift's work. Assume the population standard deviation is 6 minutes. 3. What is the probability that the company will make a Type I error using this decision rule? Round your answer to four decimal places. 0.1841 4. Using this decision rule, what is the power of the test if the actual mean time to complete the survey is 15.25 minutes? That is, what is the probability they will reject Ho when the actual average time is 15.25 minutes? Round your answer to four decimal places. 0.3446

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Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.