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How is the z-test different from z-score analysis? (Points : 1) |
The z-test compares a sample to a population.
The z-test calculates a value of z which can be compared to Table A.
The z-test provides a way to evaluate how individuals compare to a
population.
The z-test is based on how individual scores compare to a sample mean.
A one-sample t value is statistically significant in which situation? (Points : 1) |
The calculated t is equal to or larger than the table value.
The calculated t is equal to or smaller than the table value.
The calculated t is equal to or smaller than .05.
The calculated t is equal to or larger than .05.
What advantage does the one-sample t offer over the z-test? (Points : 1) |
The one sample t requires no parameter standard error of the mean.
The one sample t requires no parameter mean.
The one sample t requires no sample mean.
The one sample t doesn’t require interval scale data.
Consulting Table 3.1, what percentage of the distribution occurs below z = 1.0? (Points : 1) |
15.87%
34.13%
50%
84.13%
The Cohen’s d has an upper limit of 1.0. (Points : 1) |
True
False
What does Cohen’s d measure in the independent t-test? (Points : 1) |
Whether a result is a random outcome
The effect size of the result
The direction of the difference
The impact of the dependent variable
The z-test asks whether the population from which the sample was drawn has the same mean as the population to which it is compared. (Points : 1) |
True
False
Which of the following expressions is an indication of sampling error? (Points : 1) |
M =
m
x – M
s
M ≠ m_{M}
A type I decision error occurs in which of the following circumstances? (Points : 1) |
The decision not to proceed with an analysis
The decision to proceed when the analysis is flawed
Erroneously determining that a result is not significant
Erroneously determining that a result is significant
In a distribution for which the mean is 25 and the standard deviation is 5, what percentage of all scores occur at 30 or above? (Points : 1) |
15.87%
20%
34.13%
84.13%
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