07. Which statement best describes what a studentized residual is? O a. It is the raw difference between the observed and predicted values of the dependent variable, without any form of adjustment or standardization. O b. It involves dividing the residual of an observation by an estimate of its standard deviation, where the standard deviation is calculated excluding the observation itself from the model to minimize its influence on the measurement. O c. It is the correlation coefficient between the observed and predicted values, adjusted for the number of predictors in the model. O d. It calculates the mean absolute deviation of residuals, providing a non- parametric measure of fit for regression models. 08. The presence of unequal variances (heteroscedasticity) is one of the most common assumption violations. In these instances, the error terms (residuals) are not constant across the range of the independent variable. What is the consequence of heteroscedasticity in the residuals? O a. The lack of constant variance in the residuals biases the estimated coefficients and causes inaccurate estimation of the standard errors of the estimates, reducing statistical power. O b. The lack of constant variance in the residuals biases the estimated coefficients, but it does not cause inaccurate estimation of the standard errors of the estimates, reducing statistical power. O c. The lack of constant variance in the residuals does not bias the estimated coefficients and does not cause inaccurate estimation of the standard errors of the estimates, reducing statistical power. O d. The lack of constant variance in the residuals does not bias the estimated coefficients, but it does cause inaccurate estimation of the standard errors of the estimates, reducing statistical power