ISDS 361A

Given that X is a binomial random variable with very large n, the binomial probability P(X5) is approximated by the area under a normal curve to the right of:

4.5

8. The problem with relying on a point estimate of a population parameter is that:

A. it is virtually certain to be wrong. B. it doesn't have the capacity to reflect the effects of larger sample sizes. C. it doesn't tell us how close or far the point estimate might be from the parameter

The term 1-α refers to:

A. the probability that a confidence interval does contain the population parameter

When we have no information as to the value of p, p=.50 is used because

A. the value of p(1-p)is at its maximum value at p=.50

20. In a production facility, 10% of the parts produced are defective. With a .95 probability, the sample size that needs to be taken if the desired margin of error is 4% is

B. 217

. After constructing a confidence interval estimate for a population proportion, you believe that the interval is useless because it is too wide. In order to correct this problem, you need to:

B. increase the sample size.

If there are two unbiased estimators of a population parameter available, the one that has the smallest variance is said to be:

B. relatively efficient.

A point estimator is defined as:

C. a single value that estimates an unknown population parameter.

. If everything is held equal, and the margin of error is increased, then the sample size will

C. decrease

1. Which of the following is not a characteristic for a good estimator?

D. All of these choices are true.

Which of the following is true regarding the sampling distribution of the mean for a large sample size? Assume the population distribution is not normal.

It has the same mean as the population, but a different shape and standard deviation

Which of the following statements is false regarding the sample size needed to estimate a population proportion?

It is directly proportional to the square of the maximum allowable error B.

Which of the following is true about the sampling distribution of the sample mean?

None of these choices

A sample of size n is selected at random from an infinite population. As n increases, which of the following statements is true?

The standard error of the sample mean decreases.

A confidence interval is defined as:

a lower and upper confidence limit associated with a specific level of confidence

The expected value of the sampling distribution of the sample mean equals the population mean :

for all populations.

The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean :

is approximately normal if n > 30.

If the confidence level is reduced, the confidence interval:

narrows

The letter α in the formula for constructing a confidence interval estimate of the population proportion is:

none of these choices

The width of a confidence interval estimate of the population mean increases when the:

none of these choices

As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if:

np and n(1-p) are both greater than or equal to 5

Given a binomial distribution with n trials and probability p of a success on any trial, a conventional rule of thumb is that the normal distribution will provide an adequate approximation of the binomial distribution if:

np5 and n(1-p)5

For a sample size of 1, the sampling distribution of the mean is normally distributed:

only if the population is normally distributed.

The standard error of the sample proportion gets larger as:

p approaches 0.50

When estimating the population proportion and the value of p is unknown, we can construct a confidence interval using which of the following?

sample proportion

As a general rule in computing the standard error of the sample mean, the finite population correction factor is used only if the:

sample size is greater than 5% of the sample size

If all possible samples of size n are drawn from a population, the probability distribution of the sample mean is called the:

sampling distribution of .

If all possible samples of size n are drawn from an infinite population with a mean of and a standard deviation of , then the standard error of the sample mean is inversely proportional to:

square root n

The standard deviation of the sampling distribution of is also called the:

standard error of the sample mean

The standard deviation of is also called the:

standard error of the sample proportion

B. The sample proportion is an unbiased estimator of the population proportion.

true

The finite population correction factor should be used:

whenever the sample size is large compared to the population size.

. An unbiased estimator of a population parameter is defined as:

. An unbiased estimator of a population parameter is defined as: A. an estimator whose expected value is equal to the parameter.

estimator is consistent if...

. the difference between the estimator and the population parameter grows smaller as the sample size grows larger.