A certain drug is used to treat asthma. In a clinical trial of the​ drug, 

2020 

of 

267267 

treated subjects experienced headaches​ (based on data from the​ manufacturer). The accompanying calculator display shows results from a test of the claim that less than 

1111​% 

of treated subjects experienced headaches. Use the normal distribution as an approximation to the binomial distribution and assume a 

0.050.05 

significance level to complete parts​ (a) through​ (e) below.

​1-PropZTest

propless than<0.110.11

zequals=negative 1.832705209−1.832705209

pequals=0.03342321110.0334232111

ModifyingAbove p with caretpequals=0.07490636700.0749063670

nequals=267267

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Part 1

**a.** Is the test​ two-tailed, left-tailed, or​ right-tailed?

Right tailed test

​Two-tailed test

​Left-tailed test

To determine whether the test is two-tailed, left-tailed, or right-tailed, we need to understand the nature of the claim being tested. 

In this case, the claim is that "less than 11% of treated subjects experienced headaches."

This implies that the test is:

- **Left-tailed test:** because we are testing if the proportion is less than 0.11 (11%).

Given the context of the problem and the claim, we can conclude that the test is left-tailed.

If you have any more questions or need further details, feel free to ask!

Here are some related questions you might be interested in:
1. How do you interpret the z-value in a hypothesis test?
2. What does the p-value indicate in this context?
3. How do you calculate the test statistic for a proportion test?
4. What assumptions must be met to use the normal distribution as an approximation to the binomial distribution?
5. How do you determine the significance level in hypothesis testing?

**Tip:** In hypothesis testing, clearly understanding the direction of the test (left-tailed, right-tailed, or two-tailed) is crucial, as it influences how you interpret the test statistic and p-value.

Explore the concept of left-tailed tests in hypothesis testing for proportions with a detailed example. This page covers the basics of hypothesis testing, including how to determine if a test is left-tailed and the significance level. Includes an example with a significance level of 0.05 and test results for a proportion of 0.11.

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