At Westonci.ca, we connect you with experts who provide detailed answers to your most pressing questions. Start exploring now! Join our Q&A platform to connect with experts dedicated to providing accurate answers to your questions in various fields. Get detailed and accurate answers to your questions from a dedicated community of experts on our Q&A platform.
Sagot :
The probability that the sample proportion will differ from the population proportion by greater than 4% is 0.990.
According to the Central limit theorem, if from an unknown population large samples of sizes n > 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.
The mean of this sampling distribution of sample proportion is:
µ = p
The standard deviation of this sampling distribution of sample proportion is:
σ = √p(1-p)/n
The information provided is:
p = 0.14
n = 41
As the sample size is large, i.e n = 411 > 30. the central limit theorem can be used to approximate the sampling distribution of sampling proportion.
Compute the values of P(p^ - p >0.04) as follows:
P(p^ - p < 0.04) = P(p^-p/σ > 0.04/√0.14(1-0.14)/411
= P(Z>2.33)
= 0.990
Thus the probability that the sample proportion will differ from the population proportion by greater than 4% is 0.990
Learn more about Normal distribution here:
brainly.com/question/25638875
#SPJ4
Thank you for visiting our platform. We hope you found the answers you were looking for. Come back anytime you need more information. Thanks for using our platform. We aim to provide accurate and up-to-date answers to all your queries. Come back soon. Thank you for choosing Westonci.ca as your information source. We look forward to your next visit.