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Using Technology. In Exercises 5-8, identify the indicated values or interpret the given
display. Use the normal distribution as an approximation to the binomial distribution, as de-
scribed in Part 1 of this section. Use a 0.05 significance level and answer the following:
a. Is the test two-tailed, left-tailed, or right-tailed?
b. What is the test statistic?
c. What is the P-value?
d. What is the null hypothesis, and what do you conclude about it?
e. What is the final conclusion?
5. Adverse Reactions to Drug The drug Lipitor (atorvastatin) is used to treat high choles-
terol. In a clinical trial of Lipitor, 47 of 863 treated subjects experienced headaches (based on
data from Pfizer). The accompanying TI-83/84 Plus calculator display shows results from a
test of the claim that fewer than of treated subjects experience headaches.
pr

Ask by Ayala Rose. in the United States
Jan 23,2025

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Tutor-Verified Answer

Answer

Summary:
  • Test Type: Left-tailed
  • Test Statistic (z): -4.47
  • P-value: ≈ 0.0000035
  • Null Hypothesis (H₀): p = 0.10
  • Conclusion: Reject H₀; there is sufficient evidence to support that fewer than 10% of treated subjects experience headaches.

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Extra Insights

In the context of testing claims about proportions, the scenario involving Lipitor and headaches can be particularly intriguing. First off, this situation is a classic example where researchers need to evaluate whether a treatment causes fewer adverse reactions than expected—in this case, fewer than 10%. A two-tailed test would be appropriate if you were interested in determining whether the actual rate is significantly higher or lower than the hypothesized rate, but here, we’re only concerned if it’s lower, making it a left-tailed test.
When calculating the test statistic using the normal approximation to the binomial distribution, you’ll find that , where is the sample proportion of headaches, is the hypothesized proportion (0.10), and is the sample size (863). Using the data from your study, plug in the values and compute the z-score to assess how many standard deviations your observed proportion is from the hypothesized proportion. Then, match this to a P-value to complete your hypothesis testing journey!

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