A doctor conducts a hypothesis test to determine whether Treatment A leads to hi

Question

A doctor conducts a hypothesis test to determine whether Treatment A leads to higher patient satisfaction than Treatment B. Unfortunately, the test that is conducted results in a Type I error. In terms of the real-life implications of this experiment, what did the doctor erroneously conclude from the study, and what should the doctor have concluded? 2. 3. True/false: A researcher risks making a Type I error any time the null hypothesis is rejected. 4. Truc false: Itis easier to rejeet the null hypothesis if the researcher uses a smaller alpha (a) level. 5. True/false: A p-value is a property of the data while (significance level) is a property of tests True false: A p-value is the probability that the null hypothesis is tru that the null hypothesis is true given the sample statistic observed. we

Explanation / Answer

Ans:

Type I error:When the null hypothesis is true and you reject it, you make a type I error.

2)As,we are making type I error,it means doctor concludes that treatment A leads to a higher patient satisfaction(while in actual treatment A leads to lesser or equal patient satisfaction,as null hypothesis is true in actual.)

Doctor should have concluded that there is not significant of evidence that  treatment A leads to a higher patient satisfaction.

By making type I error,he is erroneously considering treatment A as better option.

3)True

4)False

We reject null hypothesis,when p-value<alpha.

So,smaller the alpha,we will be less likely to reject the null hypothesis.

5)True

(p-value depends on the sample data)

6)False

he P value, or calculated probability, is the probability of finding the observed, or more extreme, results when the null hypothesis (H 0) of a study question is true

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