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Vladimir [108]
2 years ago
14

According to a recent survey, 47.9 percent of housing units in a large city are rentals. A sample of 210 housing units will be r

andomly selected. Which of the following must be true for the sampling distribution of the sample proportion of housing units in the large city that are rentals to be approximately normal?
Advanced Placement (AP)
1 answer:
zysi [14]2 years ago
4 0

Answer:

B) The sample size must be greater than 30

Explanation:

According to the central limit theorem the sample size must be greater than 30 in sampling distributions to state that it is approximately normal.

Therefore, the sample size must be greater than 30 for the sampling distribution of the sample proportion of housing units in the large city that are rentals to be approximately normal.

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S fish good for the gut? Researchers tracked 22,000 male physicians for 22 years. Those who reported eating seafood of any kind
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Probably not.

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3 0
2 years ago
The average yearly snowfall in Chillyville is Normally distributed with a mean of 55 inches. If the snowfall
GuDViN [60]

Answer:

The standard deviation is 4.83 inches.

Explanation:

We are given that the average yearly snowfall in Chillyville is Normally distributed with a mean of 55 inches.  

The snowfall  in Chillyville exceeds 60 inches in 15% of the years, we have to find the standard deviation.

Let X = <u><em>the average yearly snowfall in Chillyville</em></u>.

The z-score probability distribution for the normal distribution is given by;

                                 Z = \frac{X-\mu}{\sigma}  ~ N(0,1)

where, \mu = mean amount of rainfall = 55 inches

            \sigma = standard deviation  

Now, it is stated that the snowfall  in Chillyville exceeds 60 inches in 15% of the years, that means;

        P(X > 60 inches) = 0.15

        P( \frac{X-\mu}{\sigma} > \frac{60-55}{\sigma} ) = 0.15

        P(Z > \frac{60-55}{\sigma} ) = 0.15

In the z table, the critical value of z that represents the top 15% of the area is given as  1.0364, that means;

                       \frac{60-55}{\sigma} = 1.0364

                       \sigma} = \frac{5}{1.0364} = 4.83 inches

Hence, the standard deviation is 4.83 inches.

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