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Question
Math
Posted 2 months ago

In the year 2012,12%2012,12 \% of the residents of the US moved to a different residence. Suppose that several census workers took random samples of n=150n=150 residents from the population and computed the proportion p^\hat{p} of residents in each sample who had moved in 2012.

What would be the shape of the sampling distribution of p^\hat{p} ?

Choose 1 answer:
(A) Skewed to the left
B) Skewed to the right
(C) Approximately normal
D) Uniform
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Answer from Sia
Posted 2 months ago
Solution by Steps
step 2
The CLT states that for a sufficiently large sample size, the sampling distribution of the sample proportion will be approximately normal
step 3
Given that the number of trials n=150n = 150 and the probability of success p=0.12p = 0.12, we can consider the sample size to be large enough for the CLT to apply
step 4
The mean of the sampling distribution is given by μ=np=150×0.12=18\mu = np = 150 \times 0.12 = 18
step 5
The standard deviation of the sampling distribution is given by σ=np(1p)=150×0.12×(10.12)3.97995\sigma = \sqrt{np(1-p)} = \sqrt{150 \times 0.12 \times (1 - 0.12)} \approx 3.97995
step 6
Since the sample size is large (n=150n = 150), the sampling distribution of p^\hat{p} will be approximately normal according to the CLT
C
Key Concept
Central Limit Theorem
Explanation
The Central Limit Theorem states that the sampling distribution of the sample mean (or proportion) will be approximately normal if the sample size is large enough, regardless of the population's distribution. In this case, with n=150n = 150, the sampling distribution of p^\hat{p} is approximately normal.

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