Answer on Question #61216 – Math – Statistics and Probability
Question
In the city of Hongkong 70% of the people prefer a swamp candidate for a mayoral position. supposed 30 people from Hongkong were sampled
i) What is the mean of the sampling distribution of P (sample proportion)?
ii) What is the standard error of p?
iii) What is the probability that 80% of this sample will prefer a candidate from swamp?
Solution
i) The mean of the sampling distribution of P (sample proportion) is
p ^ = 0.7 \hat{p} = 0.7 p ^ = 0.7
ii) The standard error of p is
S E = p ^ ( 1 − p ^ ) n = 0.7 ( 1 − 0.7 ) 30 = 0.083666 SE = \sqrt{\frac{\hat{p}(1 - \hat{p})}{n}} = \sqrt{\frac{0.7(1 - 0.7)}{30}} = 0.083666 SE = n p ^ ( 1 − p ^ ) = 30 0.7 ( 1 − 0.7 ) = 0.083666
iii)
Using continuity correction
P ( p n = k ) = P ( X = k ) = P ( k − 0.5 < X < k + 0.5 ) , P(pn = k) = P(X = k) = P(k - 0.5 < X < k + 0.5), P ( p n = k ) = P ( X = k ) = P ( k − 0.5 < X < k + 0.5 ) , p 1 = k − 0.5 n = 0.8 − 0.5 30 = 0.7833 , p_1 = \frac{k - 0.5}{n} = 0.8 - \frac{0.5}{30} = 0.7833, p 1 = n k − 0.5 = 0.8 − 30 0.5 = 0.7833 , p 2 = k + 0.5 n = 0.8 + 0.5 30 = 0.8167 , p_2 = \frac{k + 0.5}{n} = 0.8 + \frac{0.5}{30} = 0.8167, p 2 = n k + 0.5 = 0.8 + 30 0.5 = 0.8167 , z 1 = p 1 − p ^ S E = 0.7833 − 0.7 0.083666 = 1.00 , z_1 = \frac{p_1 - \hat{p}}{SE} = \frac{0.7833 - 0.7}{0.083666} = 1.00, z 1 = SE p 1 − p ^ = 0.083666 0.7833 − 0.7 = 1.00 , z 2 = p 2 − p ^ S E = 0.8167 − 0.7 0.083666 = 1.39. z_2 = \frac{p_2 - \hat{p}}{SE} = \frac{0.8167 - 0.7}{0.083666} = 1.39. z 2 = SE p 2 − p ^ = 0.083666 0.8167 − 0.7 = 1.39.
The random variable Z Z Z has the standard normal distribution.
The probability that 80% of this sample will prefer a candidate from swamp is
P ( p = 0.8 ) = P ( 1.00 < Z < 1.39 ) = P ( Z < 1.39 ) − P ( Z < 1.00 ) = 0.9177 − 0.8413 = 0.0764. P(p = 0.8) = P(1.00 < Z < 1.39) = P(Z < 1.39) - P(Z < 1.00) = 0.9177 - 0.8413 = 0.0764. P ( p = 0.8 ) = P ( 1.00 < Z < 1.39 ) = P ( Z < 1.39 ) − P ( Z < 1.00 ) = 0.9177 − 0.8413 = 0.0764.
Answer: i) 0.7; ii) 0.083666; iii) 0.0764.
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