The sampling distribution of P-bar is based on a normal distribution for samples of any size.
TRUE
FALSE
False
the sampling distribution of P-bar is the probability distribution of all possible values of the sample proportion P-bar
P-bar =x/n
where x is the number of elements in the sample that posses the characteristics of interest and n being the sample size.
The sampling distribution of P-bar is based on a normal distribution for samples of any size....
When samples of size n are drawn from a population, then the sampling distribution of the sample mean X̄ is approximately normal, provided that n is reasonably large. a. True b. False The interval estimate 18.5±2.5 is developed for a population mean in which the sample standard deviation s is 7.5. Had s equaled 15 instead, the interval estimate would be 37±5.0. a. True b. False
If repeated samples of a variable Y of sample size n are drawn from a normal distribution, the sampling distribution for variable Y is not distributed normally. Group of answer choices.Explain True False
Consider a sampling distribution with p=0.09 and samples of size n each. Using the appropriate formulas, find the mean and the standard deviation of the sampling distribution of the sample proportion. a. For a random sample of size n=4000. b. For a random sample of size n=1000. c. For a random sample of size n=250.
Consider a sampling distribution with p=0.09 and samples of size n each. using the appropriate formulas, find the mean and the standard deviation of the sampling distribution of the sample proportion of the following parts: A)for random sample of size n=5000 B)for random sample of size n=1000 C)for random sample of size n=500
Which of the following is not correct? For samples of any size N, the sampling distribution of the mean _____. a. has a mean equal to the mean of the raw-score population. b. is normally shaped, depending on the shape of the raw-score population and on the sample size, N. c. has a standard deviation equal to the standard deviation of the raw-score population divided by N. d. is a distribution of scores, each score of which is a sample...
Describe the sampling distribution of p. Assume the size of the population is 20,000. n = 800, p = 0.525 Describe the shape of the sampling distribution of P. Choose the correct answer below. O A. The shape of the sampling distribution of p is approximately normal because ns 0.05N and np(1 -p) 10. OB. The shape of the sampling distribution of p is approximately normal because n s 0.05N and np(1-p) < 10. OC. The shape of the sampling...
Describe the sampling distribution of p. Assume the size of the population is 30,000. n-1400, p 0.376 Describe the shape of the sampling distribution of p. Choose the correct answer belovw. O A. The shape of the sampling distribution of p is not normal because ns0.05N and np(1-p)210. O B. The shape of the sampling distribution of p is approximately normal because n s0.05N and np(1 p)10. O C. The shape of the sampling distribution of p is approximately normal...
Describe the sampling distribution of p. Assume the size of the population is 30,000. n 800, p 0.465 Describe the shape of the sampling distribution of p. Choose the correct answer below O A. The shape of the sampling distribution of p is approximately normal because n s 0.05N and np(1 -p)2 10 О с. OD. The shape of the sampling distribution of pis not normal because n s 0.05N and np(1-p)2 10. Determine the mean of the sampling distribution...
Describe the sampling distribution of p. Assume the size of the population is 25,000. n 700, p 0.548 Describe the shape of the sampling distribution of p. Choose the correct answer below. O A. O B. The The shape of the sampling distribution of p is not normal because ns 0.05N and np ( p)10 n0.05N and np(1-p)1 distribution of p is approximately normal because ns The shape of the sampling distribution of p is approximately normal because ns0.05N and...
Which of the following statements about the sampling distribution of the sample mean, x-bar, is not true? The distribution is normal regardless of the shape of the population distribution, as long as the sample size,n, is large enough. The distribution is normal regardless of the sample size, as long as the population distribution is normal. The distribution's mean is the same as the population mean. The distribution's standard deviation is smaller than the population standard deviation. All of the above...