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Sagot :
Answer:
For the Broadway actors acting in their first role on Broadway, mean: 0.184, Standard Deviation: 0.063.
For the proportion of smokers, mean = 0.167, standard deviation = 0.068
Step-by-step explanation:
Central Limit Theorem
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]
Suppose we took a survey of 38 Broadway actors and found that 18.4% of the actors we surveyed were first-timers.
This means that [tex]p = 0.184, n = 38[/tex]
What are the mean and standard deviation for the sampling distribution of p^?
Mean:
[tex]\mu = p = 0.184[/tex]
Standard deviation:
[tex]s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.184*0.816}{38}} = 0.063[/tex]
Suppose you take a random sample of 30 smokers and find that the proportion of them who are current smokers is 16.7%.
This means that [tex]n = 30, p = 0.167[/tex]
What is the mean and the standard deviation of the sampling distribution of p^ ?
Mean:
[tex]\mu = p = 0.167[/tex]
Standard deviation:
[tex]s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.167*0.833}{30}} = 0.068[/tex]
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