Question
Consider the following problem that tests a hypothesis:
A random sample of 600 teens with Facebook profiles found that 395 included photos of themselves. Let
be the proportion of teen Facebook users who included photos of themselves a profile pictures. At
significance level
, is the sample showing strong evidence that
is more than 0.59 ?
Is this testing hypothesis problem a (left-tail, right-tail, 1-tail, 2-tail) test?
left-tail test
1-tail test
2-tail test
right-tail test
Not enough information to determine.
A random sample of 600 teens with Facebook profiles found that 395 included photos of themselves. Let
be the proportion of teen Facebook users who included photos of themselves a profile pictures. At
significance level
Is this testing hypothesis problem a (left-tail, right-tail, 1-tail, 2-tail) test?
left-tail test
1-tail test
2-tail test
right-tail test
Not enough information to determine.
Ask by Campos Hanson. in the United States
Mar 21,2025
Upstudy AI Solution
Tutor-Verified Answer
Answer
This is a right-tail test.
Solution
Step 1. Define the hypotheses
We denote by the true proportion of teen Facebook users who include photos of themselves as profile pictures. The problem tests if
is more than 0.59. Thus, the hypotheses are:
We denote by
Step 2. Identify the type of test
Since the alternative hypothesis is , this is a one-tailed test. Specifically, it is a right-tail test because we are testing for an increase above 0.59.
Since the alternative hypothesis is
Step 3. Conclusion
Among the provided choices, the correct answer is:
Among the provided choices, the correct answer is:
- right-tail test
Thus, the hypothesis testing problem is a right-tail test.
Answered by UpStudy AI and reviewed by a Professional Tutor
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Mind Expander
To tackle the hypothesis that the proportion
of teen Facebook users who include photos of themselves in their profile pictures is greater than 0.59, we’re looking at a specific direction — that is, we want to determine if
is more than 0.59. This indicates that we’re conducting a right-tail test, focusing only on the upper side of the distribution for any significant differences.
In testing, it’s crucial to remember that a right-tailed test evaluates whether the sample data provides sufficient evidence to support the claim that the population proportion is greater than a specified value (in this case, 0.59). This means all of our statistical significance will be concentrated in one direction, which simplifies both our calculations and interpretations!