Degrees of freedom for the independent-measure


Complete the mcq:

Q1. Degrees of freedom for the independent-measures t statistic can be computed as df = n 1 + n 2 - 2.

True

False

Q2. For an independent-measures study comparing two samples with n = 8 in each sample, the t statistic would have df = 15.

True

False

Q3. Which of the following research situations would be most likely to use an independent-measures design?

Compare the blood-pressure readings before medication and after medication for a group a patients with high blood pressure.

Examine the long-term effectiveness of a stop-smoking treatment by interviewing subjects 2 months and 6 months after the treatment ends.

Examine the development of vocabulary as a group of children mature from age 2 to age 3.

Compare the mathematics skills for 9th grade boys versus 9th grade girls.

Q4. The null hypothesis for the independent-measures t test states

M 1 - M 2 = 0

ì 1 - ì 2 = 0

ì 1 - ì 2  0

M 1 - M 2  0

Q5. In an independent-measures t hypothesis test, how is the t statistic related to the amount of difference between the two sample means?

The larger the difference between means, the larger the value for t (farther from zero).

The magnitude of the t statistic is not related to the mean difference between samples.

The larger the difference between means, the smaller the value for t (closer to zero).

Q6. A researcher reports df = 18 for a repeated-measures t statistic. This research study used a total of n = 19 participants.

True

False

Q7. If a treatment has a consistent effect, then the sample of difference scores will have a small value for variance.

True

False

Q8. As the size of the difference scores increases, the value of the t statistic decreases (moves closer to zero).

True

False

Q9. A repeated-measures test usually is more likely to detect a real treatment effect than an independent-measures test because the repeated-measures design reduces the variance and standard error by removing individual differences.

True

False

Q10. One concern with a repeated-measures design is that a participant's performance in one treatment condition may be influenced by previous experience in another treatment condition.

True

False

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Basic Statistics: Degrees of freedom for the independent-measure
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