Using the textbook example of 420 California school districts and the regression of testscores on the student-teacher ratio, you
find that the standard error on the slope coefficient is 0.51 when using the heteroskedasticity robust formula, while it is 0.48 when employing the homoskedasticity only formula. When calculating the t-statistic, the recommended procedure is to A. use the homoskedasticity only formula because the t-statistic becomes larger B. first test for homoskedasticity of the errors and then make a decision C. use the heteroskedasticity robust formula D. make a decision depending on how much different the estimate of the slope is under the two procedures
Robust standard errors or generic White-Huber mistakes depending on this procedure. This is also recognized as the Variance Sandwich Stimator because of the appearance of the formula. Therefore, which is under homoskedasticity, robust error terms were appropriate, in which the standard deviations of its predictor variables are non-constant and are tracked across different values or linked to pre-time periods of an exponential function.
Given that the number is x, 10% increase will give us a new number of: 110/100*x =1.1x 10% decrease will give us a new number of: 90/100*1.1x =0.99x This implies the new number is less than the original number
