Connect with experts and get insightful answers to your questions on IDNLearn.com. Join our community to receive timely and reliable responses to your questions from knowledgeable professionals.
Sagot :
Answer:
The value of the standard error for the point estimate is of 0.0392.
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]
In a randomly selected sample of 100 students at a University, 81 of them had access to a computer at home.
This means that [tex]n = 100, p = \frac{81}{100} = 0.81[/tex]
Give the value of the standard error for the point estimate.
This is s. So
[tex]s = \sqrt{\frac{0.81*0.19}{100}} = 0.0392[/tex]
The value of the standard error for the point estimate is of 0.0392.
Thank you for using this platform to share and learn. Keep asking and answering. We appreciate every contribution you make. Thank you for trusting IDNLearn.com with your questions. Visit us again for clear, concise, and accurate answers.
