In using repression to predict an individuals performance on the criterion based on his or her score on the instrument, the prediction is least accurate when the correlation is:
a.-1.00
b. 0.00
c 0.50
d. 1.00
Correlation coefficients range from -1 to +1 where the two extremes enable the researcher to make almost perfect "predictions".
On the other hand, the closer the correlation coefficient approaches zero, the less reliable would be the indication of the regression line.
Can you make a choice based on the above information?
So would the correlation be 0.00
Exactly!
To determine which correlation value would result in the least accurate prediction using repression, we need to understand what repression means in this context.
Repression is a statistical concept that refers to minimizing the effects of measurement error or unreliability in a predictor variable while making predictions. It involves attenuating the correlation between the predictor variable (score on the instrument) and the criterion variable (performance) in order to estimate a more accurate prediction.
In this case, the question asks for the correlation value that would result in the least accurate prediction. Repression is most effective when the correlation between the predictor and the criterion is less than perfect (but not zero). This implies that when the correlation is strong (close to -1.00 or 1.00), repression will have less impact because the relationship between the variables is already well established.
Considering the given options:
a. A correlation of -1.00 means a perfect negative relationship, which indicates a strong association between the predictor and criterion variables. Repression is likely to have less impact in this case, so this would not be the least accurate prediction.
b. A correlation of 0.00 means no relationship between the predictor and criterion variables. Since there is no relationship to begin with, repression would not be applicable, making this the least accurate prediction.
c. A correlation of 0.50 means a moderate positive relationship between the predictor and criterion variables. Repression could potentially produce more accurate predictions in this scenario, so this would not be the least accurate prediction.
d. A correlation of 1.00 means a perfect positive relationship, indicating a strong association between the predictor and criterion variables. Similar to a correlation of -1.00, repression would have less impact in this case and is likely to result in accurate predictions.
Therefore, the option that represents the least accurate prediction is b. 0.00.