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Lesson 6 Lab

Lesson 6 Lab

Q Question 1 10 / 10 pts Question Set 1_A State the null and alternative hypotheses for the scenario above. H0: (Hint: The sign for H0 is always =) Ha: (Hint: The sign for Ha is <, >, or ?) Question 2 10 / 10 pts Question Set 1_B What is the definition of a Type I error? Question 3 10 / 10 pts Question Set 1_C What is the definition of a Type II error? Question 4 10 / 10 pts Question Set 1_D Suppose we compute a p-value and conclude that the population proportion of adult residents in this area who use the internet is greater than 0.85 (i.e. 85%), but in fact it is truly not greater than 0.85. Is this an example of a Type I error or a Type II error? Explain your answer. Question 5 10 / 10 pts Question Set 1_E The most common alpha level is 0.05. When is a higher alpha level (e.g. 0.10) typically used? Hint: See https://online.stat.psu.edu/stat200/lesson/6/6.2 Links to an external site.

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1.Your Answer: H0: P= 85% Ha: P> 85% 2.Your Answer: A Type I error is when an investigator rejects a null hypothesis which is actually true. 3.Your Answer: A Type 2 error is the error committed if the investigators fails to reject a null hypothesis which is actually false. 4.Your Answer: This is an example of Type I error. Population proportion is greater than 0.85 when it is not. Which means it is a false positive. 5.Your Answer: A higher Alpha level is used when the experiment wants more control risked when more people are involved. It will reduce Type II error.