when considering that variance is the measured difference between the predicted outcome and the actual outcome of a given situation determining homoskedasticity can help to determine which factors need to be adjusted for accuracy 
further investigation may reveal other factors that impacted scores such as to improve on the regression model the researcher would have to try out other explanatory variables that could provide a more accurate fit to the data if for example some students had seen the answers ahead of time the regression model would then have two explanatory variables time studying and whether the student had prior knowledge of the answers with these two variables more of the variance of the test scores would be explained and the variance of the error term might then be homoskedastic suggesting that the model was well defined 