What is the answer to question #2, subparts f., g., h., and i.? Thank you so much!! ### Nicotine Patch Therapy Study: Statistical AnalysisIn the study on smokers attempting to quit using nicotine patch therapy, the hypothesis is that a majority continue smoking a year after treatment. Let's analyze this:#### a. What is the null hypothesis?The null hypothesis ($H_0$) is that the proportion of smokers who continue smoking a year after treatment is 50% or less.#### b. What is the alternative hypothesis?The alternative hypothesis ($H_a$) suggests that the proportion is more than 50%.#### c. What is the value of the standard score for the sample proportion?The standard score (z-score) measures how many standard deviations an element is from the mean. This will be calculated based on sample data.#### d. What is the critical value?The critical value is a point on the scale of the test statistic beyond which we reject the null hypothesis. It is usually determined by the significance level of the test (e.g., 0.05 or 5%).#### e. What is the p-value?The p-value indicates the probability of obtaining the observed sample results, or more extreme, when the null hypothesis is true.#### f. What do you conclude?(To conclude, evaluate whether the p-value is less than the significance level to determine if you reject $H_0$. Address the claim regarding smoker behavior after therapy.)#### g. Describe a type I error for this test.A type I error occurs when the null hypothesis is true, but we reject it. In this case, it means concluding that more than 50% of the smokers continue smoking when in fact, they do not.#### h. Describe a type II error for this test.A type II error occurs when the null hypothesis is false, but we fail to reject it. Here, it means concluding that 50% or less of the smokers continue smoking when more than 50% actually do.#### i. What is the p-value if the claim is modified to state that the proportion is equal to 0.5?The p-value in this scenario would assess the probability of observing the given sample outcome under the assumption that the proportion is exactly 0.5. In a study of smokers who tried to quit smoking with nicotine patch therapy, 39 were smoking one year after the treatment, and 32 were not smoking one year after the treatment (based on data from “High Dose Nicotine Patch Therapy,” by Dale et al., *Journal of the American Medical Association*, Vol. 274, No. 17). We want to use a 0.05 significance level to test the claim that among smokers who try to quit...(Page 338, Hypothesis Testing)

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Description: What is the answer to question #2, subparts f., g., h., and i.? Thank you so much!! ### Nicotine Patch Therapy Study: Statistical AnalysisIn the study on smokers attempting to quit using nicotine patch therapy, the hypothesis is that a majority conti

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f. What do you conclude? (Be sure to address the original claim that among smokers who try to quit with nico- tine patch therapy, the majority are smoking a year the treatment.) g. Describe a type I error for this test. h. Describe a type II error for this test.

f. What do you conclude? (Be sure to address the original claim that among smokers who try to quit with nico- tine patch therapy, the majority are smoking a year the treatment.) g. Describe a type I error for this test. h. Describe a type II error for this test.

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What is the answer to question #2, subparts f., g., h., and i.?

Thank you so much!!

### Nicotine Patch Therapy Study: Statistical Analysis

In the study on smokers attempting to quit using nicotine patch therapy, the hypothesis is that a majority continue smoking a year after treatment. Let's analyze this:

#### a. What is the null hypothesis?
The null hypothesis ($H_0$) is that the proportion of smokers who continue smoking a year after treatment is 50% or less.

#### b. What is the alternative hypothesis?
The alternative hypothesis ($H_a$) suggests that the proportion is more than 50%.

#### c. What is the value of the standard score for the sample proportion?
The standard score (z-score) measures how many standard deviations an element is from the mean. This will be calculated based on sample data.

#### d. What is the critical value?
The critical value is a point on the scale of the test statistic beyond which we reject the null hypothesis. It is usually determined by the significance level of the test (e.g., 0.05 or 5%).

#### e. What is the p-value?
The p-value indicates the probability of obtaining the observed sample results, or more extreme, when the null hypothesis is true.

#### f. What do you conclude?
(To conclude, evaluate whether the p-value is less than the significance level to determine if you reject $H_0$. Address the claim regarding smoker behavior after therapy.)

#### g. Describe a type I error for this test.
A type I error occurs when the null hypothesis is true, but we reject it. In this case, it means concluding that more than 50% of the smokers continue smoking when in fact, they do not.

#### h. Describe a type II error for this test.
A type II error occurs when the null hypothesis is false, but we fail to reject it. Here, it means concluding that 50% or less of the smokers continue smoking when more than 50% actually do.

#### i. What is the p-value if the claim is modified to state that the proportion is equal to 0.5?
The p-value in this scenario would assess the probability of observing the given sample outcome under the assumption that the proportion is exactly 0.5.

In a study of smokers who tried to quit smoking with nicotine patch therapy, 39 were smoking one year after the treatment, and 32 were not smoking one year after the treatment (based on data from “High Dose Nicotine Patch Therapy,” by Dale et al., *Journal of the American Medical Association*, Vol. 274, No. 17). We want to use a 0.05 significance level to test the claim that among smokers who try to quit...

(Page 338, Hypothesis Testing)

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