Читать книгу Methods in Psychological Research - Annabel Ness Evans - Страница 92

Regression is related to correlation, but in regression, we are interested in using a predictor variable to predict a criterion variable. Continuing with the example of need for achievement and education, perhaps the researcher was also interested in predicting the need for achievement from education level. If the correlation between the two variables is statistically significant, it is a simple matter of fitting a line through the data and using the equation for the line to predict need for achievement from education level. We say “simple matter” because the calculations are all done by computer, but, certainly, the equation for a straight line is simple:

Y = mX + b

where Y is the criterion variable, X is the predictor variable, m is the slope of the line, and b is the value of Y where the line intercepts the y-axis. Be sure to keep in mind as you read the research that the accuracy of the predicted values will be as good as the correlation is. That is, the closer the correlation is to +1 (or −1), the better the predictions will be.

The statistical procedures we have been discussing all involve an a priori hypothesis about the nature of the population. Hypothesis testing is used a lot in psychology. Some other disciplines tend to prefer post hoc procedures, and you will find confidence interval estimates quite often in the literature you will be reading.