Posted: April 12th, 2016

1. What is meant by the phrase: strength of the correlation?

How much highs on one variable go with highs on the other

How much highs on one variable go with lows on the others

How much lows on one variable go with lows on the other

All of the above

2. All of the following are reasons why Z scores are used to help determine the degree of linear correlation EXCEPT:

Z scores give a standard indication of just how high or low each score is

The sum of the cross products of Z scores gives you a large positive number if there is a positive correlation and a large negative number if there is a negative correlation

Because of the nature of Z scores, the cross product will be positive in all cases

Using Z scores allows you to compare scores on different measures

3. When is the correlation coefficient zero?

It is never zero

When there is no linear correlation

When there is a perfect positive linear correlation

When there is a perfect negative linear correlation

4. Which of the following represents the strongest linear correlation?

+.09

+.88

.92

.18

5. You want to study the physical effects of caffeine. To recruit participants for your experiment you post a sign up sheet for anyone willing to participate. This is an example of:

Random selection

Haphazard selection

Stratified selection

Type B selection

6. If you want to know something about a population, your results would be MOST accurate if you could study the:

Entire population

Subgroup from the population

Top 5% of people from the population

Top 50% of the people from the population

7. A researcher tests effects of a new training program. The hypothesis that this new training program will work better than the old training program is called the:

Comparison hypothesis

Null hypothesis

Research hypothesis

There is no special name for this kind of hypothesis

8. The cutoff Z score on the comparison distribution is 1.64 and the sample value has a score of 1.32 on the comparison distribution.

The null hypothesis can not be rejected

The null hypothesis is rejected

The research hypothesis is supported

The research hypothesis is rejected

9. What is a correct argument for using a two tailed test even if there is a clear basis for predicting a result in a given direction?

If the null hypothesis is in fact true, a failure to reject it will give stronger evidence in support of it.

One tailed tests cannot be used in almost any real study involving two groups.

If an unexpected result comes out opposite to what is predicted, it does not have to be ignored.

A two tailed test gives you a better chance of getting a significant result.

10. In most behavioral and social science research articles, unless the researcher specifically states that a _____________ test was used, it is assumed that it was a(n) _______________.

Tow tailed; one tailed

One tailed; two tailed

.10 significance test; .25 significance test

.05 significance test; .01 significance test

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