Practice quizzes & Posttests FInal Exam Flashcards
(120 cards)
1
Q
Which inferential test should be used to compare two sample means to each other?
The two-sample t-test
The ratio of IQRs
The one-sample z-test
The one-sample t-test
A
The two-sample t-test
2
Q
The most important difference between Cohen’s d and the t-test is that Cohen’s d…
can only be used for large samples (n > 30).
is not affected by sample size.
can only be used for two-group situation.
requires the population variance.
A
is not affected by sample size.
3
Q
What is the formula for the degrees of freedom (df) for a two-sample t-test?
n - 1
n - 2
n - k - 1
√n
A
n - 2
4
Q
If a researcher wants to compare the effects of an antidepressant to the effects of a placebo on levels of anxiety, then what is the independent variable (that is, the IV)?
Two-sample t-test
Antidepressant medication
Levels of anxiety
Medication: antidepressant vs. placebo
A
Medication: antidepressant vs. placebo
5
Q
When the means of two groups are the same, then Cohen’s d…
will equal 0.
is equal to the combined sample sizes.
cannot be calculated.
will approach infinity.
A
will equal 0.
6
Q
A two-sample t-test is an appropriate test when..
two samples are being compared on an interval or ratio level variable.
the data contain open-ended or undefined scores.
two samples are being compared on a nominal or ordinal level variable.
a sample mean being compared to a population mean
A
two samples are being compared on an interval or ratio level variable.
7
Q
Imagine that a researcher conducts a one-tailed (i.e., directional) two-sample t-test with a critical value of -1.83 and gets an observed value (or test value) of t = +1.98. What is the proper conclusion in this case?
Retain the null hypothesis
Reject the null hypothesis
The researcher should use a two-tailed (i.e., nondirectional) test
Cannot be determined without additional information
A
Retain the null hypothesis
8
Q
Cohen’s d indicates the number of…
standard errors between two means.
matching observations in two samples.
different observations in two samples.
standard deviations between two means.
A
standard deviations between two means.
9
Q
If a researcher wants to compare the effects of an antidepressant to the effects of a placebo on levels of anxiety, then what is the dependent variable (that is, the DV)?
Levels of anxiety
Medication: antidepressant vs. placebo
Two-sample t-test
Antidepressant medication
A
Levels of anxiety
10
Q
If a researcher gathers data from participants before and after they participate in an exercise training program and wants to know whether their performance scores improved, then he should use…
a one-tailed, one sample t-test.
a two-tailed, two-sample t-test.
a one-tailed, repeated measures t-test.
a two-tailed, repeated measures t-test.
A
a one-tailed, repeated measures t-test.
11
Q
If a research conducts an inferential test (such as a t-test) and retains (i.e., fails to reject) the null hypothesis, then what is the probability of a Type I error?
0.00
.05
1.00 - p
1.00
A
0.00
12
Q
One assumption of the two-sample t-test is that…
the data have a uniform distribution.
the two samples are independent of one another.
a two-tailed test will be used.
the two samples are as similar as possible.
A
the two samples are independent of one another.
13
Q
Imagine that a researcher conducts a two-sample t-test with critical values of ±2.10 and gets an observed value (or test value) of t = 1.98. What is the proper conclusion in this case?
The research should use a z-test instead
Retain the null hypothesis
Reject the null hypothesis
Cannot be determined without additional information
A
Retain the null hypothesis
14
Q
If a researcher wants to compare the effects of an antidepressant to the effects of a placebo on levels of anxiety, then what is the grouping variable?
Medication: antidepressant vs. placebo
Antidepressant medication
Levels of anxiety
Two-sample t-test
A
Medication: antidepressant vs. placebo
15
Q
The comparison group in a repeated measures t-test is…
grouping variable.
each person’s own score at time 1.
the difference between each person’s time 1 and time 2 scores.
the mean for the general population.
A
each person’s own score at time 1.
16
Q
Imagine that a researcher conducts a repeated measures t-test with critical values of ±2.78 and gets an observed value (or test value) of t = -3.30. What is the proper conclusion in this case?
Reject the null hypothesis
This is an impossible value of t for a repeated measures test
Retain the null hypothesis
Cannot be determined without additional information
A
Reject the null hypothesis
17
Q
When the means of two samples are being compared and Cohen’s d = 0, then…
the means are identical.
n must be 0 also.
the distributions must have the same standard deviation as well as the same mean.
there is no variation in the data.
A
the means are identical.
18
Q
If a research conducts an inferential test (such as a t-test) and rejects the null hypothesis, then what is the probability of a Type II error?
0.00
1.00 - p
1.00
.05
A
0.00
19
Q
If n = ∞, then what is the critical value of t for alpha = .05?
±3.30
±1.96
0.00
Cannot be determined without additional information
A
±1.96
20
Q
If a researcher conducts a t-test with an alpha of .01 and gets a p-value of .25, then the researcher should…
retain (i.e, fail to reject) the null hypothesis.
transform the data.
switch to the standard alpha of .05.
reject the null hypothesis.
A
retain (i.e, fail to reject) the null hypothesis.
21
Q
If you want to compare the means of two different groups to each other then you should use…
a two-sample t-test.
the ratio of standard errors.
a one-sample z-test.
a one-sample t-test.
A
a two-sample t-test.
22
Q
What is the formula for the degrees of freedom (df) for a two-sample t-test?
n - 1
n - k -1
n - 2
A
n-2
23
Q
As the means of two groups become more similar, Cohen’s d will…
approach 0.
become positively skewed.
approach infinity.
become impossible to calculate.
A
approach 0.
24
Q
If you conduct a one-tailed (i.e., directional) two-sample t-test with a critical value of +2.20 and gets an observed value of t = -3.53, then what should you do?
Cannot be determined without additional information
Use a two-tailed (i.e., nondirectional) test instead
Retain the null hypothesis
Reject the null hypothesis
A
Retain the null hypothesis
25
If you conducted an experiment to compare the effects of two different online ad campaigns on the number of clickthroughs (i.e., how often people clicked on each ad), then what is the dependent variable (DV)?
Online samples
Ad campaign
The number of clickthroughs
Two-sample t-test
The number of clickthroughs
26
If you conduct an inferential test and retain the null hypothesis, then what is the chance of a Type I error?
0.00
.05
1.00
alpha
0.00
27
Imagine that you conduct a two-sample t-test with critical values of ±2.30 and gets an observed value (or test value) of t = -2.09. What should you do?
Retain the null hypothesis
Cannot be determined without additional information
Use a z-test instead
Reject the null hypothesis
Retain the null hypothesis
28
The comparison group in a repeated-measures t-test is...
the grouping variable.
each person’s own score at time 1.
the mean for the general population.
the difference between each person’s time 1 and time 2 scores.
each person’s own score at time 1.
29
If n = ∞, then what is the critical value of t for alpha = .05?
±1.96
0.00
t cannot be used when n = ∞
∞
±1.96
30
When the means of two samples are being compared and Cohen’s d = 1.10, then...
you should reject the null hypothesis.
the means are 1.1 standard deviations apart.
an error was made because d can never be greater than ±1.00.
t will be statistically significant.
the means are 1.1 standard deviations apart.
31
The analysis of variance (or ANOVA) is the preferred inferential test when you need to...
compare the means of three or more groups.
standardize all of the scores.
compare the scores of a group of participants before and after a manipulation
find the association between two quantitative variables.
compare the means of three or more groups.
32
If an ANOVA is statistically significant, what does that mean?
The variance of the group means is less than 0.
The group means are all different from one another.
The variance of the group means is equal to 0.
The variance of the group means is greater than 0.
The variance of the group means is greater than 0.
33
What is the symbol for the test statistic in ANOVA?
F
p
z
t
F
34
What is the most common measure of effect size for ANOVA?
eta-squared
Cohen’s d
z
The standard error
eta-squared
35
In order to calculate eta-squared, you first need to know...
the sum of squares (SS).
whether the F test is statistically significant.
Cohen’s d.
the shape of the distribution.
the sum of squares (SS).
36
The analysis of variance is useful if you want to...
compare the number of men and women in different political parties.
compare the mean incomes of people in several different jobs.
test the change in scores for a group of people before and after an intervention.
compare the mean income of men and women.
compare the mean incomes of people in several different jobs
37
The version of ANOVA that is used to compare, for example, the well-being of people from the three largest countries in North America is called the...
three-way ANOVA.
one-way ANOVA.
population ANOVA.
factorial ANOVA.
one-way ANOVA.
38
What is the null hypothesis for ANOVA?
All group distributions are identical
The differences between groups are smaller than the differences within groups
All group means are equal
All group means are equal
39
Imagine a study that compared men and women (the gender factor) and who were social liberal or conservative (the social attitudes factor) on levels of empathy. If there were significant differences between men and women, regardless of social attitudes, then the gender factor would be called...
a significant main effect.
a spurious effect.
a significant interaction effect.
a significant manipulation effect.
a significant main effect.
40
In order to conduct an ANOVA, the dependent variable (DV) must be...
a continuous variable.
an interval or ratio level variable.
a nominal variable.
a ratio level variable only.
an interval or ratio level variable.
41
Why is it better to use a one-way ANOVA than multiple t-tests to compare the means of several groups?
ANOVA handles missing data better
ANOVA handles large sample sizes better
Multiple t-tests inflate the Type I error rate
Multiple t-tests inflate the Type II error rate
Multiple t-tests inflate the Type I error rate
41
Which of the following numbers is a possible value for eta-squared?
.16
-3.30
-0.39
1.96
.16
42
If an ANOVA is conducted and eta-squared is .10, then...
10% of the variance in the DV can be predicted by the IV(s).
10% of the scores on the DV can be correctly predicted.
10% of the scores have missing values.
the null hypothesis should be retained.
10% of the variance in the DV can be predicted by the IV(s).
43
Imagine a study that compared men and women (the gender factor) and who were social liberal or conservative (the social attitudes factor) on levels of empathy. If there were significant differences between people with liberal and conservative social attitudes, regardless of gender, then the attitude factor would be called...
a significant manipulation effect.
a significant interaction effect.
a spurious effect.
a significant main effect.
a significant main effect.
44
What is the purpose of a post-hoc test?
To determine whether there are any interaction effects.
To calculate the effect size, eta-squared.
To determine whether the sample size was sufficient.
To find out which groups (or combinations of groups) are different from each other
To find out which groups (or combinations of groups) are different from each other
45
When calculating probability values for ANOVA, the correct distribution is the...
t distribution.
F distribution.
standard normal distribution.
p distribution.
F distribution.
46
When it is appropriate to conduct post-hoc tests?
Whenever an ANOVA is not statistically significant
Whenever an ANOVA is statistically significant
Whenever eta-squared is greater than 1
Whenever the data are normally distributed
Whenever an ANOVA is statistically significant
47
Imagine a study that compared men and women (the gender factor) and who were social liberal or conservative (the social attitudes factor) on levels of empathy. If the the difference between men and women was different for people who were social liberal or conservative, then this result would be called...
a spurious effect.
a significant main effect.
a significant manipulation effect.
a significant interaction effect.
a significant interaction effect.
48
What effects are shown in this chart? (pic #1)
Factor A: significant main effect; Factor B: significant main effect; AxB: no interaction
Factor A: significant main effect; Factor B: significant main effect; AxB: significant interaction
Factor A: no main effect; Factor B: significant main effect; AxB: no interaction
Factor A: significant main effect; Factor B: no main effect; AxB: no interaction
Factor A: no main effect; Factor B: significant main effect; AxB: no interaction
49
What effects are shown in this chart? (pic#2)
Factor A: no main effect; Factor B: no main effect; AxB: no interaction
Factor A: significant main effect; Factor B: significant main effect; AxB: significant interaction
Factor A: no main effect; Factor B: no main effect; AxB: significant interaction
Factor A: significant main effect; Factor B: significant main effect; AxB: no interaction
Factor A: no main effect; Factor B: no main effect; AxB: significant interaction
50
If you use an ANOVA to compare the means of four groups and you get a statistically significant result, what does that mean?
The variance of the group means is less than 0.
The group means are all different from one another.
The variance of the group means is equal to 0.
The variance of the group means is greater than 0.
The variance of the group means is greater than 0.
51
If you need to calculate an effect size for ANOVA, what would the best choice be?
The standard error
z-scores
Cohen’s d
eta-squared
eta-squared
52
The analysis of variance would be appropriate if you wanted to...
compare the mean income of people in one state to a national average.
test the change in scores for people before and after an intervention.
compare time to graduation for people at different universities.
compare the number of men and women in different college majors.
compare time to graduation for people at different universities.
53
What is the null hypothesis for ANOVA?
SS mean = SS within
All group distributions are identical
All group means are equal
The differences between groups are smaller than the differences within groups
All group means are equal
54
If you want to use an ANOVA, your outcome variable should be...
a quantitative variable.
a manipulated variable.
a categorical variable.
uniformly distributed.
a quantitative variable.
55
Why is it better to use a one-way ANOVA than multiple t-tests to compare the means of several groups?
The Type II error rate gets too big with multiple t-tests
ANOVA is better suited for categorical outcome variables
The Type I error rate gets too big with multiple t-tests
It is not possible to compare several different groups with multiple t-tests
The Type I error rate gets too big with multiple t-tests
56
Imagine a study that compared athletes and nonathletes who went to schools with or without football teams on donation levels after graduation. If there were significant differences between athletes and nonathletes, regardless of whether their school had a football team, then result for the athlete factor would be called...
a spurious effect.
a significant manipulation effect.
a significant main effect.
a significant interaction effect.
a significant main effect.
57
Which distribution is used to get probability values for ANOVA?
The F distribution
The p distribution
The t distribution
The standard normal distribution
The F distribution
58
What effects are shown in this chart?
EXAM #2 pic
Factor A: significant main effect; Factor B: significant main effect; AxB: significant interaction
Factor A: no main effect; Factor B: no main effect; AxB: significant interaction
Factor A: significant main effect; Factor B: significant main effect; AxB: no interaction
Factor A: no main effect; Factor B: no main effect; AxB: no interaction
Factor A: no main effect; Factor B: no main effect; AxB: significant interaction
59
Imagine a study that compared men and women (the gender factor) and who were right handed or left handed (the handedness factor) on brain function. If the the difference between right-handed and left-handed people was different for men and women, then this result would be called...
a significant main effect.
a significant interaction effect.
a spurious effect.
a significant manipulation effect.
a significant interaction effect.
60
If the dots on a scatterplot generally extend from the bottom left to the upper right of the diagram but are very widely spread out, the researcher would report the correlation as:
Strong and negative
Close to zero
Weak and positive
Strong and positive
Weak and positive
61
The relationship in this scatterplot is...
EXAM #3 PIC
open-ended
nonlinear
linear
direct.
nonlinear
62
What is the minimum level of measurement to calculate a Pearson’s r correlation coefficient?
Nominal
Ratio
Ordinal
Interval
Interval
63
What is the non-directional null hypothesis for correlation?
r > 0 (or rho > 0)
r = 1 (or rho = 1)
r = 0 (or rho = 0)
r < 1 (or rho < 1)
r = 0 (or rho = 0)
64
What is the predicted value of Y when X = 10 using this regression equation?
Y = 30 - 1.2*X
18
28.8
10
Cannot be calculated without additional information
18
65
Correlations (using the Pearson product moment correlation coefficient) may be uninterpretable and inappropriate if the data...
are inversely related.
are interval level.
come from a sample with n < 20.
have a nonlinear relationship.
have a nonlinear relationship.
66
The difference between a predicted Y score and an actual observed Y score is known as the...
All of the answers are correct
error ratio.
residual.
imperfection coefficient.
residual.
67
If the dots on a scatterplot are spread out randomly, the researcher would report the correlation as:
Strong and positive
Weak and negative
Close to zero
Weak and positive
Close to zero
68
Which of the following is an impossible value for R2?
.36
.16
1.10
.00
1.10
69
If the mean of X is 42, the mean of Y = 72, and rxy= 0, then what is the predicted value of Y when X = 30?
42
72
0
Cannot be predicted without additional information
72
70
Which of the following is true about regression towards the mean?
Predicted Y values will not always be perfect unless r = ± 1
Predicted Y values tend to be closer to the mean of Y than the observed values of X are to the mean of X
Predicted Y values will have less variation than actual observed values of Y
All of the answers are correct
All of the answers are correct
71
When people who score low on one variable tend to score low on another variable, then those two variables...
have a significant main effect.
have a significant interaction.
are negatively correlated.
are positively correlated.
are positively correlated.
72
If X and Y in a regression equation are both expressed as z scores – zX and zY – and the correlation between the two variables is r = .3, then what is the predicted value of zY when zX = - 1.2?
3.6
-0.36
-1.23
Cannot be determined without additional information
-0.36
73
If X and Y in a regression equation are both expressed as z scores – Zx
and Zy– then what can never happen?
Zy > 1
Zy > Zx
Zy = Zx
Zy > Zx
Zy > Zx
74
If a person has a middling score on X but a very high score on Y, what would their effect on the regression equation be?
They would raise the intercept but not change the slope
They would raise the intercept and raise the slope
They would not change the intercept but they would raise the slope
They would no predictable effect on either the intercept or the slope
They would raise the intercept but not change the slope
75
Which of the following illustrates a negative correlation?
The more often a person visits the dentist, the fewer cavities they have.
The less often a person gets sick, the less sick days they would need to take off work.
As a person writes less, the quality of their writing decreases.
The more often a person exercises, the more muscle mass they will accumulate.
The more often a person visits the dentist, the fewer cavities they have.
76
If r = .65, then the members in a sample who have _____ values on the independent variable have _____ values on the dependent variable.
Lower, higher
No relationship
Lower, lower
Higher, lower
Lower, lower
77
What is the predicted value of Y when X = 120 using this regression equation?
Y = -350 + 5*X
950
Cannot be calculated without additional information
475
250
250
78
The vertical distance between a person’s predicted score on Y and their actual score on Y is called _____ and it signifies _____.
the deviation; the average of how far each score is from the regression line
displacement; regression to the mean
the residual; error in prediction
the standard error; error in measurement
the residual; error in prediction
79
Which statistic is defined as the proportion of variance accounted in the dependent variable by the independent variable?
Chi-squared
Range
R-squared
Mode
R-squared
80
If the dots on a scatterplot generally extend from the top left to the bottom right of the diagram but are very widely spread out, the researcher would report the correlation as...
negative but weak.
negative and strong.
positive and strong.
positive but weak.
negative but weak.
81
What is the minimum level of measurement to calculate Pearson’s r correlation coefficient?
Ratio
Interval
Nominal
Ordinal
Interval
82
What is the predicted value of Y when X = 20 using this regression equation?
Y = 12 - 0.8*X
224
11.2
-4
-16
-4
83
When a regression equation doesn’t predict a person’s score perfectly, then the difference between their predicted score and their actual score is the...
error ratio.
residual.
deviation.
measurement error.
residual.
84
Which of the following is an impossible value for
?
1.00
-.01
.00
.99
-.01
85
Which of the following is true about regression towards the mean?
Predicted Y values will not be perfectly accurate unless r = ± 1
Predicted Y values will have less variation than observed values of Y
All of the answers are correct
Predicted Y values tend to be closer to the mean of Y than the observed values of X are to the mean of X
All of the answers are correct
86
If X and Y in a regression equation are both expressed as z scores – Zx
and Zy - and the correlation between the two variables is r = -.2, then what is the predicted value of Zy when Zx= - 0.5?
1.0
-0.1
0.1
-0.5
0.1
87
If a regression equation is calculated for a sample of data and then a person who is an outlier on both X and Y is added, what would likely happen to the regression equation?
The new score would likely change both the intercept and the slope
The new score would likely change the slope but not the intercept
The new score would likely change the intercept but not the slope
The new score would have no predictable effect on either the intercept or the slope
The new score would likely change both the intercept and the slope
88
If r = -.4, then the people who have _____ values on the predictor variable generally have _____ values on the outcome variable.
lower, lower
higher, higher
lower, higher
moderate, unpredictable
lower, higher
89
The vertical distance between a person’s predicted score on Y and their actual score on Y is called _____ and it signifies _____.
the standard error; error in measurement
displacement; regression to the mean
the residual; error in prediction
the deviation; the average of how far each score is from the regression line
the residual; error in prediction
90
If you want to see whether the distribution of declared majors for incoming freshman matches a school’s historic distribution of majors, then which version of the chi-squared test should you use?
You should use ANOVA for this question
The chi-squared goodness of fit test
The chi-squared test for independence
The chi-squared distribution test
The chi-squared goodness of fit test
91
The chi-squared tests are examples of...
methods for overcoming sampling bias.
descriptive statistics.
inferential statistics.
imputational methods.
inferential statistics.
92
What is the null hypothesis for the chi-squared test for independence?
Each group on the predictor variable (or IV) will have identical proportions in each category of the outcome variable (or DV)
Each group’s frequencies will be distributed uniformly across all categories
The mean of group 1 is the same as the mean of group 2
The distribution of frequencies on the outcome variable will match a hypothesized pattern
Each group on the predictor variable (or IV) will have identical proportions in each category of the outcome variable (or DV)
93
Which of the following does NOT require a degrees of freedom calculation?
t-test
ANOVA
chi-squared
z-test
z-test
94
If you were to conduct a chi-squared test for independence using an alpha of .01 and you got an observed p-value of .02, then you...
have proven that the alternative hypothesis is true.
have proven that the null hypothesis is true.
should reject the null hypothesis.
should retain the null hypothesis.
should retain the null hypothesis.
95
In calculating a chi-squared tests, the observed frequencies in each category are compared to...
standardized frequencies.
uniform frequencies.
the population mean.
expected frequencies.
expected frequencies.
96
In a study that looks at the relationship between handedness and intellectual giftedness (which, by the way, are related), a statistically significant chi-squared test for Independence would mean...
that post-hoc t-tests are needed to untangle the patterns.
only that the distribution of handedness varied by giftedness.
that the distribution of giftedness varied by handedness and the distribution of handedness varied by giftedness.
only that the distribution of giftedness varied by handedness.
that the distribution of giftedness varied by handedness and the distribution of handedness varied by giftedness.
97
The degrees of freedom for chi-squared tests are based on...
the sample size.
the largest category in the variable(s).
the number of categories in the variable(s).
normally distributed data.
the number of categories in the variable(s).
98
The chi-squared tests are called “non-parametric” tests because...
they do not make assumptions about population parameters.
they rely on unknown population parameters.
they rely on orthogonal eigenvectors.
they do not make inferences about populations.
they do not make assumptions about population parameters.
99
One of the major advantages of the chi-squared tests is that they...
transform the data into normal distributions.
compensate for missing data.
do not require probability values for inferential testing.
can be used with nominal, ordinal, interval, or ratio data.
can be used with nominal, ordinal, interval, or ratio data.
100
A chi-squared test is conducted when...
the population mean and sample mean are known.
three or more samples are being compared.
two sample means are being compared.
both of the variables are nominal/ordinal data.
both of the variables are nominal/ordinal data.
101
Which version of the chi-squared test is good for examining the relationship between two variables?
The chi-squared test for independence
The chi-squared goodness of fit test
No version of chi-squared works for relationships
The chi-squared correlational test
The chi-squared test for independence
102
The probability distribution that is used in the chi-squared test is the...
z-distribution
F-distribution.
chi-squared distribution.
t-distribution
chi-squared distribution.
103
The chi-squared tests are...
used to impute/replace missing data.
inferential statistics/procedures.
methods of data transformation.
descriptive statistics/procedures.
inferential statistics/procedures.
104
If a researcher conducts a chi-squared test for independence using an alpha of .01 and gets an observed p-value of .04, then he...
should retain (i.e., fail to reject) the null hypothesis.
should reject the null hypothesis.
needs to gather new data.
has proven that the null hypothesis is true.
should retain (i.e., fail to reject) the null hypothesis.
105
What is the null hypothesis for the chi-squared test for independence?
Each group on the predictor variable (or IV) will have identical proportions in each category of the outcome variable (or DV)
Each group’s frequencies will be distributed uniformly across all categories
The distribution of frequencies on the outcome variable will match a hypothesized pattern
The mean of group 1 is the same as the mean of group 2
Each group on the predictor variable (or IV) will have identical proportions in each category of the outcome variable (or DV)
106
What is the minimum level of measurement required for either of the chi-squared tests?
Interval
Nominal
Ordinal
Ratio
Nominal
107
Which inferential test does NOT require a degrees of freedom calculation?
ANOVA
t-test
z-test
chi-squared
z-test
108
The word “independence” in the chi-squared test for independence means...
it is impossible to predict the distribution of scores on the outcome/dependent variable.
the distribution of frequencies on the outcome/dependent variable is unrelated to the categories of the predictor/independent variable.
the experimenter has control over which categories people are assigned to on the predictor/independent variable.
frequencies are distributed at random across categories of the outcome/dependent variable.
the distribution of frequencies on the outcome/dependent variable is unrelated to the categories of the predictor/independent variable.
109
If a researcher conducts a chi-squared test for independence using an alpha of .05 and gets an observed p-value of .04, then she...
has proven that the null hypothesis is false.
should reject the null hypothesis.
should retain (i.e., fail to reject) the null hypothesis.
has proven that the alternative hypothesis is true.
should reject the null hypothesis.
110
What is the null hypothesis for the chi-squared goodness of fit test?
The distribution of frequencies will be zero for all categories
The distribution of frequencies will match a hypothesized pattern of expected scores or frequencies
The distribution of frequencies will be the same for people in each predictor group
The distribution of frequencies will be uniform across all categories
The distribution of frequencies will match a hypothesized pattern of expected scores or frequencies
111
In calculating a chi-squared tests, the observed frequencies in each category are compared to...
expected frequencies.
standardized frequencies.
the population mean.
uniform frequencies.
expected frequencies.
112
Which of the following situations is appropriate for using a chi-squared test?
To examine the relationship between major and graduation status at a university
To compare average heights of males and females
To compare a sample's mean IQ scores with the known population mean IQ score
To examine the relationship between height and weight
To examine the relationship between major and graduation status at a university
113
In a study that looks at the relationship between gender and college major, a statistically significant chi-squared test for independence would mean...
only that the distribution of genders varied by college major.
that the distribution of college major varied by gender and the distribution of genders varied by college major.
only that the distribution of college major varied by gender.
that post-hoc t-tests are needed to untangle the patterns.
that the distribution of college major varied by gender and the distribution of genders varied by college major.
114
The most common measure of effect size for the chi-squared test for independence is...
the multiple correlation.
eta-squared.
the square root of chi-squared.
the phi coefficient.
the phi coefficient.
115
Which of the following null hypothesis statistical tests require calculating degrees of freedom?
One-sample t-test
Chi-squared
All of these tests
Two-sample t-test
ALL OF THESE TESTS
116
If a researcher conducts a chi-squared goodness-of-fit test using an alpha of .05 and gets an observed p-value of .10, then she..
should reject the null hypothesis.
should retain (i.e., fail to reject) the null hypothesis.
has proven that the null hypothesis is false.
has proven that the alternative hypothesis is true.
should retain (i.e., fail to reject) the null hypothesis.
117
The chi-squared tests are called “non-parametric” tests because...
they rely on orthogonal eigenvectors.
they do not make inferences about populations.
they rely on unknown population parameters.
they do not make assumptions about population parameters.
they do not make assumptions about population parameters.
118
In order to understand exactly how strong the relationship is between two categorical variables in a chi-squared test for independence, a research should use...
the standardized mean difference.
the standard error.
the size of the observed p-value.
a measure of effect size like the phi coefficient.
a measure of effect size like the phi coefficient.
119
A major advantage of the chi-squared tests is that they...
are based on means.
compensate for missing data.
can be used with any level of measurement.
do not use probability distributions.
can be used with any level of measurement.
