In order to approximate the probability of a sample proportion, which of the following
needs to be true:
A.
np > 10
B.
np > 30
C.
np > 10 and nq > 10
D.
nq > 10
E.
We can always approximate the probability of a sample proportion.
Conditions of narmality for sample proportion are
np > 10 and n q > 10 , Where q = ( 1 - p)
In order to approximate the probability of a sample proportion, which of the following needs to...
The normal distribution can be used to approximate the binomial distribution. In order to use the normal approximation, np and nq must be greater than or equal to 5. A correction for continuing must also be used true or false
fouTube Maps Your Turn The proportion of left-handed people in the general population is about 0.1. Suppose a random sample of 225 people is observed Using our "rule of thumb." can we use normal approximation values for this sampling distribution? No • * * and nq = 98 * (Click to view hint) What is the mean of the sample proportion? * (Click to view hint) np = 7 My = 768 What is the standard error? = 76 *...
1.) Which of the following conditions on the sample size will guarantee that a binomial approximation to the Normal Distribution will be very accurate? Select all that apply. a.) np> 5 b.) n>5 c.) nq > 5 d.) n greater than and equal 5 2.) Find the probability that in 200 rolls of a fair die, we observe 85 or less even numbers.
A random sample of size n 200 yielded p 0.50 a. Is the sample size large enough to use the large sample approximation to construct a confidence interval for p? Explain b. Construct a 95% confidence interval for p C. Interpret the 95% confidence interval d. Explain what is meant by the phrase "95% confidence interval." a. Is the sample large enough? AYes, because np 2 15 and nq2 15 No, because np 2 15 and nq< 15 No, because...
If a sample size is greater than 30, which of the following characteristics of the distribution of sample means is true? a.) Nothing can be assumed about the distribution of sample means. b.) The sample size needs to be increased by 10% so we can apply the Central Limit Theorem. c.) The distribution of sample means has a binomial distribution. d.) The distribution of sample means is approximately normal.
The population proportion is 0.65. What is the probability that a sample proportion will be within £0.01 of the population proportion for each of the following sample sizes? Round your answers to 4 decimal places. Use z-table. a. n = 100 b. n = 200 c. n = 500 d.n= 1,000 e. What is the advantage of a larger sample size? With a larger sample, there is a higher probability will be within £0.01 of the population proportion p.
For the following four questions, is it appropriate to use a normal distribution to approximate a confidence interval for the population proportion? If it’s inappropriate, indicate why. A clothing store owner wants to know the proportion of customers who used coupons within the last year. He selects in a random order all 2,000 receipts from a database of all purchases within the last year and finds that 340 of them are discounted by coupons. Select one: a. Yes. b. No,...
The population proportion is .50 . What is the probability that a sample proportion will be within +/- .04 of the population proportion for each of the following sample sizes? Round your answers to 4 decimal places. Use z-table. a. n= 100 b .n= 200 c. n= 500 d. n= 1000
a) Sketch the area under the standard normal curve over the indicated interval and find the specified area. (Round your answer to four decimal places.) The area to the right of z = 1.51 is ____ b) The Customer Service Center in a large New York department store has determined that the amount of time spent with a customer about a complaint is normally distributed, with a mean of 9.5 minutes and a standard deviation of 2.1 minutes. What is...
The population proportion is .45. What is the probability that a sample proportion will be within +/- 0.03 of the population proportion for each of the following sample sizes? Round your answers to 4 decimal places a. n = 100 b. n = 200 c. n = 500 d. n = 1000