QBA chapters 8,9, and 10

The ability of an interval estimate to contain the value of the population parameter is described by the

confidence level

The power curve provides the probability of

correctly rejecting the null hypothesis

The p-value

must be a number between zero and one

In order to use the normal distribution for interval estimation of u when standard deviation is known and the sample is very small, the population

must have a normal distribution

In order to use the normal distribution of interval estimation of u when the standard deviation is known and the sample is very small, the population

must have a normal distribution

When constructing a confidence interval for the population mean and the standard deviation of the sample is used, the degrees of freedom for the t distribution equals

n-1

A sample of 200 elements from a population with a known standard deviation is selected. For an interval estimation of u, the proper distribution to use is the

normal distribution

The standard error of Xbar1-Xbar2 is the

standard deviation of the sampling distribution of Xbar1-Xbar2

The standard error of Xbar1 - Xbar2 is the

standard deviation of the sampling distributions of Xbar1-Xbar2

If the level of significance of a hypothesis test is raised from .01 to .05, the probability of a Type 2 Error

will decrease

To construct an interval estimate for the difference between the means of two populations when the standard deviations of the two populations are unknown and it can be assumed the two populations have equal variance, we must use a t distribution with (let n1 be the size of sample 1 and n2 be the size of sample 2)

(n1+n2-2)degrees of freedom

For a lower bounds one-tailed test, the test statistic z is determined to be zero. The p-value for this test is

+0.5

If we want to provide a 95% confidence interval for the mean of a population, the confidence coefficient is

0.95

When the following hypotheses are being tested at a level of significance of a Ho: u >= 500 Ha: u < 500 the null hypothesis will be rejected if the p-value is

< = a

The probability of making a Type 2 Error is denoted by

B

After computing a confidence interval, the user believes the results are meaningless because the width of the interval is too large. What is the best recommendation?

Increase the sample size

When developing an interval estimate for the difference between two sample means, with sample sizes of N1 and N2

N1 and N2 can be different sizes

What maximizes the value of P(1-P)?

P=0.50

The error of rejecting a true null hypothesis is

a Type 1 Error

An interval estimate is a range of values used to estimate

a population parameter

If we are interested in testing whether the proportion of items in population 1 is larger than the proportion of items in population 2, the

alternative hypothesis should state P1-P2 > 0

A 95% confidence interval for a population mean is determined to be 100 to 120. If the confidence coefficient is reduced to 0.90, the interval for u

becomes narrower

In interval estimation, as the sample size becomes larger, the interval estimate

becomes narrower

As the number of degrees of freedom for a t distribution increases, the difference between the t distribution and the standard normal distribution

becomes smaller

If two independent large samples are taken from two populations, the sampling distribution of the difference between the two sample means

can be approximated by a normal distribution

As the sample size increases, the margin of error

decreases

As the test statistic becomes larger, the p-value

gets smaller

To compute an interval estimate for the difference between the means of two populations, the t distribution

is not restricted to small sample situations

An assumption made about the value of a population parameter is called a

hypothesis

After computing a confidence interval, the user believes the results are meaningless because the width of the interval is too large. What is the best recommendation

increase the sample size

The valued added and subtracted from a point estimate in order to develop an interval estimate of the population parameter is known as the

margin of error

When each data value in one sample is matched with a corresponding data value in another sample, the samples are known as

matched samples

A sample size of 200 elements from a population with a known standard deviation is selected. For an interval estimation of u, the proper distribution to use is the

normal distribution

The sampling distribution of Pbar1 - Pbar2 is approximated by a

normal distribution

The p-value is a probability that measure the support (or lack of support) for the

null hypothesis

A two-tailed test is performed at 95% confidence. The p-value is determined to be 0.09. The null hypothesis

should not be rejected

When "S" is used to estimate the standard deviation, the margin of error is computed by using

t distribution

Whenever the population standard deviation is unknown and the population has a normal or near normal distribution, which distribution is used in developing an interval estimation?

t distribution

From a population that is normally distributed, a sample of 25 elements is selected and the standard deviation of the sample is computed. For the interval estimation of u, the proper distribution is to use the

t distribution with 24 degrees of freedom

Independent, simple random samples are taken to test then difference between the means of two populations whose standard deviations are not known, but are assumed to be equal. The sample sizes are N1 = 25 N2=35. The correct distribution to use is the

t distribution with 58 degrees of freedom

Independent simple random samples are taken to test the difference between the means of two populations whose variances are not known, but are assumed to be equal. the samples sizes are n1=32 n2=40. The correct distribution to use is the

t distribution with 70 degrees of freedom

The probability of committing a Type 1 error when the null hypothesis is true is

the Level of Significance

In hypothesis testing, if the null hypothesis is rejected

the alternative hypothesis is true

In hypothesis testing, if the null hypothesis has been rejected when the alternative hypothesis has been true

the correct decision has been made

In the hypothesis testing procedure, a (sign looks like an a) is

the level of significance

What does NOT need to be known in order to compute the p-value

the level of significance

In determining the sample size necessary to estimate a population proportion, what is not needed

the mean of the population

For the interval estimation of u when standard deviation is known and the sample is large, the proper distribution to use is

the normal distribution

Whenever using the t distribution for interval estimation (when the sample size is very small ), we must assume that

the population is approximately normal

Whenever using the t distribution for interval estimation (when the sample size is very small), we must assume that

the population is approximately normal

A sample of 2o items from a population with an unknown standard deviation is selected in order to develop an interval estimate of u. What is NOT necessary?

the sample must have a normal dstribution

From a population that is not normally distributed and whose standard deviation is not known, a sample of 6 items is selected to develop an interval estimate for the mean of the population

the sample size must be increased

In developing an interval estimate, if the population standard deviation is unknown

the sample standard deviation can be used

In interval estimation, the t distribution is applicable only when

the sample standard deviation is used to estimate the population standard deviation

The absolute value of the difference between the point estimate and the population parameter it estimates is

the sampling error

If we change a 95% confidence interval estimate to a 99% confidence interval estimate, we can expect

the size of the confidence interval to increase

In hypothesis testing

the smaller the type1 error, the larger the type 2 error will be

For a two-tail test, the p-value is the probability of obtaining a value for the test statistic as

unlikely as that provided by the sample

If a hypothesis is rejected at 95% confidence, it

will always be rejected at 90% confidence

The p-value ranges between

zero to one