Question

Fill in the blanks:

In studies conducted to assess how well the GRE (Graduate Record Examination) predicts graduate school GPA (grade point average), the GRE is considered the __________ variable and the GPA is the __________ variable.

To establish the concurrent validity of a newly-developed instrument, we can ___________ it with a well-established instrument which measures the same thing.

Correlating the scores from a newly-developed short version of a personality inventory with a similar full-length personality inventory may be used to establish the ____________ validity of the short-version inventory.

When a test simply appears to measure what it is intended to measure, we conclude that the test has a high __________ validity.

In assessing an instrument’s criterion-related validity, the relationship between the instrument and the criterion is indicated by the __________ coefficient.

When an instrument systematically discriminates against a group of test-takers, the test is considered _________.

Answer 1

There are 6 statements, I wil denote the statement number and corresponding fill in the blanks.

1)GRE is considered predictor variable and the GPA is criterion variable.

2)correlate

3)concurrent

4)face

5)vailidity

6)biased

Explanation:

Predictor variable can be considered as an independent variable which affects the dependent variable. Here we are predicting GPA with GRE so GRE is predictor variable ( used to predict) and GPA is criterion variable.

Be corrrelating it with a established instrument we can determine how accurate the instrument is depending upon the correlation. It should have a high positive correlation (>0.9) for good accuracy.

Concurrent validity measures how well the current measurement correspond to a previously established measurement.

Face validity denotes whether a instrument really measures what it says it measures.

Validity coefficient denotes how useful the measurement instrument is when predicting the criterion.

Biased instruments discriminates against a particular case. For example a biased coin which has a higher probability for heads than tails.

That is all the answers. Happy learning.