Question description

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.

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

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 ≠ mM

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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