PSY625 test 1Quizlet Review
If we calculated an effect size and found it was r = .21 which expression would best
describe the size of effect?
large
b.
small
c.
small to medium
d.
medium to large - answer -c. small to medium
What is the relationship between sample size and the standard error of the mean?
a.
The standard error decreases as the sample size increases.
b.
The standard error decreases as the sample size decreases.
c.
The standard error is unaffected by the sample size.
d.
The standard error increases as the sample size increases. - answer -a.
The standard error decreases as the sample size increases.
Of what is p the probability?
a.
p is the probability of observing a test statistic at least as big as the one we have if there
were no effect in the population (i.e., the null hypothesis were true).
b.
p is the probability that the results are due to chance, the probability that the null
hypothesis (H0) is true.
c.
p is the probability that the results are not due to chance, the probability that the null
hypothesis (H0) is false.
d.
p is the probability that the results would be replicated if the experiment was conducted
a second time. - answer -a.
p is the probability of observing a test statistic at least as big as the one we have if there
were no effect in the population (i.e., the null hypothesis were true).
In general, as the sample size (N) increases:
a.
The confidence interval is unaffected
b.
The confidence interval becomes less accurate.
c.
, The confidence interval gets narrower.
d.
The confidence interval gets wider. - answer -c.
The confidence interval gets narrower.
Power is the ability of a test to find an effect of a certain size.
True
False - answer -True
A Type I error occurs when:
a.
The data we have typed into SPSS is different from the data collected.
b.
We conclude that there is an effect in the population when in fact there is not.
c.
We conclude that there is not an effect in the population when in fact there is.
d.
We conclude that the test statistic is significant when in fact it is not. - answer -b.
We conclude that there is an effect in the population when in fact there is not.
What does a significant test statistic tell us?
a.
There is an important effect.
b.
That the test statistic is larger than we would expect if there were no effect in the
population.
c.
The hull hypothesis is false.
d.
All of the above. - answer -b.
That the test statistic is larger than we would expect if there were no effect in the
population.
Of what is the standard error a measure?
a.
The variability of scores in the population.
b.
The 'flatness' of the distribution of sample scores.
c.
The variability of sample estimates of a parameter.
d.
The variability in scores in the sample. - answer -c.
The variability of sample estimates of a parameter.
Under a null hypothesis, a sample value yields a p-value of .015. Which of the following
statements is true?
If we calculated an effect size and found it was r = .21 which expression would best
describe the size of effect?
large
b.
small
c.
small to medium
d.
medium to large - answer -c. small to medium
What is the relationship between sample size and the standard error of the mean?
a.
The standard error decreases as the sample size increases.
b.
The standard error decreases as the sample size decreases.
c.
The standard error is unaffected by the sample size.
d.
The standard error increases as the sample size increases. - answer -a.
The standard error decreases as the sample size increases.
Of what is p the probability?
a.
p is the probability of observing a test statistic at least as big as the one we have if there
were no effect in the population (i.e., the null hypothesis were true).
b.
p is the probability that the results are due to chance, the probability that the null
hypothesis (H0) is true.
c.
p is the probability that the results are not due to chance, the probability that the null
hypothesis (H0) is false.
d.
p is the probability that the results would be replicated if the experiment was conducted
a second time. - answer -a.
p is the probability of observing a test statistic at least as big as the one we have if there
were no effect in the population (i.e., the null hypothesis were true).
In general, as the sample size (N) increases:
a.
The confidence interval is unaffected
b.
The confidence interval becomes less accurate.
c.
, The confidence interval gets narrower.
d.
The confidence interval gets wider. - answer -c.
The confidence interval gets narrower.
Power is the ability of a test to find an effect of a certain size.
True
False - answer -True
A Type I error occurs when:
a.
The data we have typed into SPSS is different from the data collected.
b.
We conclude that there is an effect in the population when in fact there is not.
c.
We conclude that there is not an effect in the population when in fact there is.
d.
We conclude that the test statistic is significant when in fact it is not. - answer -b.
We conclude that there is an effect in the population when in fact there is not.
What does a significant test statistic tell us?
a.
There is an important effect.
b.
That the test statistic is larger than we would expect if there were no effect in the
population.
c.
The hull hypothesis is false.
d.
All of the above. - answer -b.
That the test statistic is larger than we would expect if there were no effect in the
population.
Of what is the standard error a measure?
a.
The variability of scores in the population.
b.
The 'flatness' of the distribution of sample scores.
c.
The variability of sample estimates of a parameter.
d.
The variability in scores in the sample. - answer -c.
The variability of sample estimates of a parameter.
Under a null hypothesis, a sample value yields a p-value of .015. Which of the following
statements is true?
