Practice quizzes & Posttests Exam 2

Question 1

One reason that researchers nearly always gather data from samples of participants instead of entire populations is because..
it can be impractical or even impossible to study populations.
samples provide more accurate data than populations.
population parameters are generally biased.
samples have larger means than populations.

Answer 1

it can be impractical or even impossible to study populations.

Question 2

According to the Central Limit Theorem, the mean of the sampling distribution of means – Ux
– will equal…
the mean of the original population.
the mean of the original population divided the square root of n.
the mean of the original population divided by n-1.
Cannot be predicted without additional information.

Answer 2

the mean of the original population.

Question 2

If a test has a population mean of 70 and standard deviation of 6, then what is the z-score for a sample of n = 9 scores with a mean of 76?
3
2
1
6

Answer 2

3

Question 3

The central limit theorem says that when all possible samples of a sufficient size are taken from a population and their means are charted, that distribution of means will be…
standardized.
uniformly distributed.
normally distributed.
platykurtic.

Answer 3

normally distributed.

Question 4

The distribution of all possible samples of a given size (e.g., n = 54 or n = 117) are taken from a population and their means are charted, that distribution is known as…
the sample distribution.
the sampling distribution of means.
the mean of the population.
a standard mean distribution.

Answer 4

the sampling distribution of means.

Question 5

The standard error is…
the population mean divided by n-1.
a common mistake in coding responses.
the standard deviation of the sampling distribution.
the measure of sample bias.

Answer 5

the standard deviation of the sampling distribution

Question 6

If a distribution of raw scores has a strong negative skew, then, given a sufficiently large n, the sampling distribution of means for that distribution will…
be normal.
be uniform.
have a strong negative skew.
have a strong positive skew.

Answer 6

be normal.

Question 7

The distribution of all possible sample means (of a given size) is called…
the sampling distribution of means.
the distribution of means.
the population of raw scores.
the distribution of samples.

Answer 7

the sampling distribution of means

Question 7

If a person were to create a sampling distribution for sample standard deviations, then the mean of that distribution would be equal to…
cannot be calculated without additional information.
the square root of the standard deviation of the original distribution.
the mean of the original distribution.
the standard deviation of the original distribution.

Answer 7

the standard deviation of the original distribution.

Question 8

If a distribution has a mean of 100 and a standard deviation of 15, then what is the standard error for a sample of 225 scores?
1
125
15
cannot be calculated without additional information

Answer 8

1

Question 9

If a distribution has a mean of 30 and a standard deviation of 3, then what is the z-score for a sample of 4 scores with a mean of 27?
1.5
2
-3
-2

Answer 9

-2

Question 10

The Central Limit Theorem states that the shape of a sampling distribution becomes closer to what shape as the number of sample means in the distribution increases?
Normal
Uniform
Skewed
Bimodal

Answer 10

Normal

Question 11

If the population mean for a distribution is 150 and the standard deviation is 20, then what is the z-score for a sample of 100 people with an average score of 153?
50
0.15
3
1.5

Answer 11

1.5

Question 12

If a population has a mean of 40 and a standard deviation of 8, what would the z-score be for a sample of 16 people with a mean of 46?
6
4
3
2

Answer 12

3

Question 13

A sampling distribution can be calculated for…
population means only.
sample means only.
any sample statistic.
any population parameter.

Answer 13

any sample statistic.

Question 14

The equation for the standard error of a sampling distribution is.

Answer 14

σ/√n.

Question 15

What is the symbol for the standard error?

Answer 15

σx̅

Question 15

What is the standard error of a distribution if
= 20 and n = 25?
-5
0.80
4
5

Answer 15

4

Question 16

If a population has a mean of 60 and a standard deviation of 15, what is the z-score for a sample of 9 people with an average of 55?
-1
15
-0.33
-5

Answer 16

-1

Question 17

As the size of samples (n) in a sampling distribution increases, the shape of that distribution becomes more…
variable.
uniform.
similar to the original population distribution.
normal.

Answer 17

Normal

Question 18

What is the z-score for a sample with n = 100 and M = 103 if the population parameters are
u =100 and o=10?
0.0
+3
Cannot be calculated
+1

Answer 18

+3

Question 19

What does the symbol µ¯x
refer to?
The mean of the sampling distribution of means
The standard deviation of the sampling distribution of standard deviations
The standard deviation of the sampling distribution of means
The mean of the sampling distribution of standard deviations

Answer 19

The mean of the sampling distribution of means

Question 20

What is the standard error for a distribution with
= 40 when n = 4?

20
40
10
160

Answer 20

20

Question 21

If a distribution of raw scores has a strong positive skew, then, given a sufficiently large n, the mean of the sampling distribution will be equal to the _____ of the raw score distribution.
median
mean
mode

Answer 21

mean

Question 22

One reason that researchers nearly always gather data from samples of participants instead of populations is because..
any group with n < 1000 is a sample.
populations always contain missing data.
data analysis is easier for samples than for populations.
it is easier to gather data from samples than populations.

Answer 22

it is easier to gather data from samples than populations.

Question 23

According to the Central Limit Theorem, if a research takes sufficiently large samples (e.g., n > 30) from a bimodal distribution, then the resulting sampling distribution will be…
platykurtic.
uniform.
bimodal.
unimodal.

Answer 23

unimodal.

Question 24

The distribution of all possible sample variances (of a given sample size) is called…
the sampling distribution of variances.
the variance differential.
the sample variance.
the population variance.

Answer 24

the sampling distribution of variances.

Question 25

The distribution of all possible sample variances – if n is sufficiently large (e.g., n > 30) – will be…
leptokurtic.
mesokurtic.
positively skewed.
uniform.

Answer 25

mesokurtic.

Question 26

The standard error of a sampling distribution is a function of two things:
The sample size and the sample range.
The degrees of freedom and the degree of normality.
The population standard deviation and the sample size
The population size and the sample variance.

Answer 26

The population standard deviation and the sample size

Question 27

As the size of samples in a sampling distribution increases (i.e., as n get bigger), then that distribution becomes…
more similar to the shape of the original population distribution.
wider.
flatter.
narrower.

Answer 27

narrower.

Question 28

If a researcher used a one-sample z-test to determine whether an experimental group was different from a general population, what she would actually be testing is…
whether their distribution had any overlap
whether their standard errors were different.
whether their distributions had the same shape.
whether their means are different.

Answer 28

whether their means are different.

Question 29

When calculating an effect size for the z-test…
the sample data must be normally distributed.
z must have an absolute value greater than 2.
the sample size must be large (n > 100).
it is most common to use Cohen’s d.

Answer 29

it is most common to use Cohen’s d.

Question 30

A Type I error is also called…
a true positive
a false positive
a true negative
a false negative

Answer 30

a false positive

Question 31

Which level of alpha for a hypothesis test has the lowest risk of a Type I error?
.01
.05
.10
Cannot be determined without additional information

Answer 31

.01

Question 31

If a researcher is using an critical value of
1.96 for a z-test and gets an observed z (i.e., test value) of +0.55 for a sample of n = 40, then the researcher should…
reach no conclusion without additional data.
reject the alternative hypothesis.
retain (i.e., fail to reject) the null hypothesis.
reject the null hypothesis.

Answer 31

retain (i.e., fail to reject) the null hypothesis.

Question 32

Imagine two studies that are identical in every respect except the size of their samples. Sample A has an effect size of d = .40 and p-value of .001. Sample B also has an effect size of d = .40 but a p-value of .10. Which sample likely had the larger sample size?
Sample A
They are the same
Cannot be determined without additional information
Sample B

Answer 32

Sample A

Question 33

If a person’s blood sample tests positive for a disease when, in fact, the person does not have the disease, then…
a Type II error has occurred.
a Type I error has occurred.
a testing error has been made.
the procedure must not have been conducted correctly.

Answer 33

a Type I error has occurred.

Question 33

If a researcher is using alpha = .01 and gets a p-value for the z-test of p = .005, then…
the researcher has proven that the alternative hypothesis is true.
the researcher should conclude that the results are unlikely to occur by chance if the null hypothesis is true.
the researcher has proven that the null hypothesis is false.
the researcher should conclude that the results are likely to occur by chance if the null hypothesis is true.

Answer 33

the researcher should conclude that the results are unlikely to occur by chance if the null hypothesis is true.

Question 33

In order to compute a one-sample z-test you must…
calculate the sample standard deviation.
first know whether the sample mean is different from the population mean.
know the population standard deviation.
have a large sample (n > 100)

Answer 33

know the population standard deviation.

Question 34

If a sample’s mean really is different from the comparison population’s mean, then what is the easiest way to make sure that the null hypothesis would be rejected?
Getting as large a sample as possible
Getting as uniform a sample as possible
Getting as representative a sample as possible
Getting as varied a sample as possible

Answer 34

Getting as large a sample as possible

Question 35

“Estimation” refers to a class of…
robust statistics.
descriptive statistics.
sample statistics.
inferential statistics.

Answer 35

inferential statistics.

Question 36

How is the point estimate affected when the sample standard deviation increases?
It becomes lower
It becomes narrower
It becomes higher
It does not change

Answer 36

It does not change

Question 37

Imagine that samples – Sample A with n = 20 and Sample B with n = 200 – are drawn from the same population and confidence intervals are computed for the same variables, which sample will likely have the more precise confidence interval?
They will be the same
Cannot answer without additional information
Sample B
Sample A

Answer 37

Sample B

Question 37

How is a confidence interval affected when the sample standard deviation decreases?
It becomes less biased
It increasingly resembles a normal distribution
It becomes narrower
It becomes wider

Answer 37

It becomes narrower

Question 38

When the range of confidence for a confidence interval becomes lower - from 90% to 80%, for example - then the confidence interval will…
become narrower.
be less biased.
become wider.
be more difficult to calculate.

Answer 38

become narrower.

Question 39

What is the point estimate for the population mean if the population standard deviation is 24, the sample size is 36, and the sample mean is 110?
110
86-136
106-114
Cannot be calculated without additional information

Answer 39

110

Question 39

As the mean for a distribution increases, then the width of the corresponding confidence interval will…
become wider.
become more biased.
stay the same.
become narrower.

Answer 39

stay the same.

Question 39

Imagine a sample with n = 49 and a mean of 60 that comes from a population with a standard deviation of 7. Based on these data, what would be the 99.9% confidence interval for the population mean? (Use z-score of +3.29 for the 99.9% confidence level.)
60
(39.67, 83.03)
(59.53, 60.47)
(56.71, 63.29)

Answer 39

(56.71, 63.29)

Question 40

The sample mean is ________ and a confidence interval for the mean is _______.
a descriptive statistic; an inferential statistic
a sample value; also a sample value
for n < 100 only; for n > 100 only
a biased measure; an unbiased measure

Answer 40

a descriptive statistic; an inferential statistic

Question 41

Which is more precise (in the statistical sense): a point estimate or a confidence interval?
A confidence interval
Cannot be determined without additional information
They are the same
A point estimate

Answer 41

A point estimate

Question 42

The z-test is appropriate when…
the researcher needs to estimate the population variance/standard deviation
the researcher knows the population mean and variance/standard deviation
the data distribution is symmetrical.
the data consist of nominal variables.

Answer 42

the researcher knows the population mean and variance/standard deviation

Question 43

If a researcher wants to test whether an experimental group is different from the general population, the she would test…
the hypothesis that the experimental group has a lower score than the population.
whether her sample was representative.
the hypothesis that the experimental group has a higher score than the population.
the null hypothesis of no difference between the group and the population.

Answer 43

the null hypothesis of no difference between the group and the population.

Question 43

In a two-tailed or non-directional test, if the critical value has a greater absolute value than the observed (or test) value does, the the null hypothesis…
must be replaced with a one-tailed or directional hypothesis.
is not rejected (i.e., retained).
is rejected.
is proven false.

Answer 43

is not rejected (i.e., retained).

Question 44

When calculating an effect size for the z-test…
you must first check for homogeneity of variance.
the alpha values must be incorporated.
the sample size is irrelevant.
you must use the population standard error.

Answer 44

the sample size is irrelevant.

Question 45

What does it mean when the result of a z-test is called “statistically significant”?
The null hypothesis has been proven false
The alternate hypothesis has been proven true
The alpha value was greater than the p-value
The results can be generalized to other populations

Answer 45

The alpha value was greater than the p-value

Question 45

If a researcher is using an critical value of ±1.96 for a z-test and gets an observed (or test) z of -1.73, then the researcher should…
retain (i.e., fail to reject) the null hypothesis.
use a one-tailed test instead.
change the critical value to a smaller value.
reject the null hypothesis.

Answer 45

retain (i.e., fail to reject) the null hypothesis.

Question 46

If a researcher is using an alpha of .05 for a z-test and gets an observed (or test) p-value of .23, then the researcher should…
change the alpha to a larger value.
use a one-tailed test instead.
retain (i.e., fail to reject) the null hypothesis.
reject the null hypothesis.

Answer 46

retain (i.e., fail to reject) the null hypothesis.

Question 47

When choosing a level of alpha for a hypothesis test, unless you have a compelling reason to do otherwise, you should use…
.01
.05
.50
.10

Answer 47

.05

Question 48

A Type II error occurs when…
the sample data lead us to retain (i.e., fail to reject) a null hypothesis that is false.
the sample is too small for significance testing.
the sample data lead us to reject a null hypothesis that is true.
the sample data are biased in a systematic way.

Answer 48

the sample data lead us to retain (i.e., fail to reject) a null hypothesis that is false

Question 48

A Type I error occurs when…
the sample data are biased in a systematic way.
the sample is too small for significance testing.
the sample data lead us to reject a null hypothesis that is true.
the sample data lead us to retain (i.e., fail to reject) a null hypothesis that is false.

Answer 48

the sample data lead us to reject a null hypothesis that is true.

Question 49

Imagine that a researcher is interested in whether residents in his local area have higher levels of well-being than the national average. What would be an appropriate alternate hypothesis for a one-tailed or directional z-test for this test?
local residents average = national average
local residents average > national average
None of these choices are appropriate
local residents average < national average

Answer 49

local residents average > national average

Question 49

Imagine two studies that are identical in every respect except the size of their samples. Sample A has an effect size of d = .20 and a p-value of .03. Sample B has an effect size of d = .20 and a p-value of .005. Which sample likely had the smaller sample size?
Cannot be determined without additional information
Sample B
Sample A
They are the same

Answer 49

Sample A

Question 49

Imagine two studies that are identical in every respect except their effect sizes. Sample A has a sample size of n = 80 and a p-value of .01. Sample B has a sample size of n = 80 and a p-value of .10. Which sample likely had the larger effect size?
They are the same
Sample B
Sample A
Cannot be determined without additional information

Answer 49

Sample A

Question 49

When the mean of the population that a sample comes from does not differ from the general population but the sample mean is nonetheless significantly different from the general population, then…
the researcher should gather new data.
a Type I error has occurred.
a Type II error has occurred.
a sampling error has been made.

Answer 49

a Type I error has occurred.

Question 50

If a researcher is comparing a sample mean to a population mean and gets Cohen’s d = -2.0, this means that…
a mistake was made because Cohen’s d cannot be negative.
the sample mean is two standard errors away from the population mean.
the effect is statistically significant.
the sample mean is two standard deviations below the population mean.

Answer 50

the sample mean is two standard deviations below the population mean.

Question 50

If a researcher is using alpha = .05 and gets a p-value for the z-test of p = .02, then…
this proves that the null hypothesis is false.
Cohen’s d = alpha/p = .05/.02 = 2.5
the results are unlikely to occur by chance if the null hypothesis is true.
the results are likely to occur by chance if the null hypothesis is true.

Answer 50

the results are unlikely to occur by chance if the null hypothesis is true.

Question 51

If a research conducts a z-test and does not reject the null hypothesis, then…
it is not appropriate to calculate an effect size.
the researcher must gather new data.
the researcher has proven that the null hypothesis is true.
None of the other choices is correct.

Answer 51

None of the other choices is correct.

Question 51

A researcher who wants to use a z-test to compare a sample mean to a population mean must first…
delete any outliers from the sample data.
recruit a diverse sample of participants.
choose measures that yield ratio level data.
know the population standard deviation.

Answer 51

know the population standard deviation.

Question 52

If you draw a picture of the null distribution with the critical values and regions of rejection marked, then the alpha level is represented by…
the location of the observed sample values.
the height of the distribution at the critical values.
the proportion of the distribution between the critical values.
the proportion of the distribution in the regions of rejection.

Answer 52

the proportion of the distribution in the regions of rejection.

Question 52

If a researcher believes that the null hypothesis is false and wants to have the greatest chance of rejecting it with their study, then which of the following would make it more likely that the null hypothesis would be rejected?
Decreasing the effect size
Increasing n
Decreasing n
Increasing the critical value

Answer 52

Increasing n

Question 53

When we talk about “estimation” in statistics, what is it that is being estimated?
A population parameter
The degree of sampling bias
The values for missing data
A sampling distribution

Answer 53

A population parameter

Question 53

What is one important difference between a point estimate and a confidence interval?
The point estimate is based on sample data instead of population data
The confidence interval is used only for unbiased statistics instead of biased ones
The point estimate cannot be used for inferring population values
The confidence interval gives two numbers instead of one

Answer 53

The confidence interval gives two numbers instead of one

Question 54

How is a point estimate affected when the sample size increases?
It becomes higher
It does not change
It becomes narrower
It becomes lower

Answer 54

It does not change

Question 55

Imagine a sample with n = 25 and a mean of 55 that comes from a population with a standard deviation of 10. Based on these data, what would be the 95% confidence interval for the population mean? (Use z-scores of ±1.96 for the 95% confidence level.)
(51.08, 58.92)
(53.00, 57.00)
(53.04, 56.96)
(54.22, 55.78)

Answer 55

(51.08, 58.92)

Question 56

Imagine that two samples – Sample A with n = 20 and Sample B with n = 200 – are drawn from the same population and confidence intervals are computed for the same variables, which sample will have the narrower confidence interval?
Cannot answer without additional information
They will be the same
Sample B
Sample A

Answer 56

Sample B

Question 57

If you can use only one number to estimate a population parameter, then the best value is a…
point estimate.
null hypothesis.
confidence interval.
probability value.

Answer 57

point estimate.

Question 58

How is a confidence interval affected when the sample size increases?
It becomes wider
It becomes narrower
It becomes less biased
It increasingly resembles a normal distribution

Answer 58

It becomes narrower

Question 59

Imagine two samples that are drawn from the same population and measure the same variables in the same way. Sample A has a larger confidence interval than Sample B does. Which sample likely has the larger n?
Sample A
Sample B
They are the same
Cannot be determined without additional information

Answer 59

Sample B

Question 60

When the range of confidence for a confidence interval becomes higher – from 80% to 99%, for example – then the confidence interval will…
become wider.
be more difficult to calculate.
become narrower.
be less accurate.

Answer 60

become wider.

Question 61

Imagine a sample with n = 64 and a mean of 121 that comes from a population with a standard deviation of 16. Based on these data, what would be the 80% confidence interval for the population mean? (Use z-scores of ±1.28 for the 80% confidence level.)
(118.44, 123.56)
(119.72, 122.28)
(119.00, 123.00)
(120.68, 121.32)

Answer 61

(118.44, 123.56)

Question 62

What is the point estimate for the population mean if the population standard deviation is 10, the sample size is 100, and the sample mean is 80?
78-82
Cannot be calculated without additional information
80
70-90

Answer 62

80

Question 63

For which measures is it possible to compute a confidence interval?
Only unbiased measures
Any population parameter
Only measures with normally distributed scores
Only the population mean

Answer 63

Any population parameter

Question 63

As the standard deviation for a distribution increases, then the corresponding confidence interval will…
become wider.
become more biased.
stay the same.
become narrower.

Answer 63

become wider.

Question 64

As the mean for a sample becomes greater, the width of the corresponding confidence interval will…
stay the same.
decrease.
become undefined.
increase.

Answer 64

stay the same.

Question 65

Imagine a sample with n = 49 and a mean of 183 that comes from a population with a standard deviation of 21. Based on these data, what would be the 99.9% confidence interval for the population mean? (Use z-scores of ±3.29 for the 99.9% confidence level.)
(173.13, 192.87)
(179.71, 186.29)
(180.00, 186.00)
(181.59, 184.41)

Answer 65

(173.13, 192.87)

Question 66

Imagine a sample with n = 400 and a mean of 68 that comes from a population with a standard deviation of 20. Based on these data, what would be the 90% confidence interval for the population mean? (Use z-scores of ±1.64 for the 90% confidence level.)
(67.92, 68.08)
(67.00, 69.00)
(48.00, 88.00)
(66.36, 69.64)

Answer 66

(66.36, 69.64)

Question 67

A confidence interval specifies a range of values for a parameter estimate, whereas a(n) _____ specifies just a single value for that parameter.
nominal estimate
inferential statistic
point estimate
sample value

Answer 67

point estimate

Question 68

Which is generally more precise (in the statistical sense): a point estimate or a confidence interval?
They are the same
A confidence interval
Cannot be determined without additional information
A point estimate

Answer 68

A point estimate

Question 69

Which is generally more accurate (in the statistical sense): a point estimate or a confidence interval?
They are the same
A point estimate
A confidence interval
Cannot be determined without additional information

Answer 69

A confidence interval

Question 70

A point estimate for the population mean is based on…
normally distributed data only.
the sample size.
the sampling distribution of means.
the sample mean.

Answer 70

the sample mean.