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