For the given scenario, determine the type of error that was made, if any. (Hint: Begin by determining the null and alternative hypotheses.) A pharmaceutical company claims only 2% as the percentage of people taking a particular drug that experience significant side effects. One researcher claims that the percentage of people taking a particular drug that experience significant side effects is less than 2%. The researcher conducts a hypothesis test and rejects the null hypothesis. Assume that in reality, the percentage of people taking a particular drug that experience significant side effects is 0.5 % . Was an error made? If so, what type?

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For the given scenario, determine the type of error that was made, if any. (Hint:
Begin by determining the null and alternative hypotheses.)
A pharmaceutical company claims only 2% as the percentage of people taking a
particular drug that experience significant side effects. One researcher claims that
the percentage of people taking a particular drug that experience significant side
effects is less than 2%. The researcher conducts a hypothesis test and rejects the
null hypothesis. Assume that in reality, the percentage of people taking a particular
drug that experience significant side effects is 0.5 %. Was an error made? If so,
what type?
Transcribed Image Text:For the given scenario, determine the type of error that was made, if any. (Hint: Begin by determining the null and alternative hypotheses.) A pharmaceutical company claims only 2% as the percentage of people taking a particular drug that experience significant side effects. One researcher claims that the percentage of people taking a particular drug that experience significant side effects is less than 2%. The researcher conducts a hypothesis test and rejects the null hypothesis. Assume that in reality, the percentage of people taking a particular drug that experience significant side effects is 0.5 %. Was an error made? If so, what type?
OYes; Type II error
O Yes; Type I error
O No; correct decision
Transcribed Image Text:OYes; Type II error O Yes; Type I error O No; correct decision
Expert Solution
Step 1

Type 1 error: When the null hypothesis is rejected even when it is true, this is known as a Type I error.   The significance level α determines the risk of making this error. Another term used for type 1 error is "false-positive.".

Type 2 error: If the researcher does not reject a null hypothesis that is actually wrong in the population, this is known as a type II error. Another term used for type 2 error is "false-negative".

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