A researcher has estimated the relationship between salaries of 100 selected employees of an organization (shown as "EARN" in $/hour) and their years of education (shown as "YRSEDUC", in years) as per...

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Extracted text: A researcher has estimated the relationship between salaries of 100 selected employees of an organization (shown as "EARN" in $/hour) and their years of education (shown as "YRSEDUC", in years) as per the following regression outcome with 5% level of significance (numbers are made up): Model 1: OLS, using observations 1-100 Dependent variable: EARN coefficient std. error t-ratio p-value const 3.32418 1.00223 3.317 0.0009 *** YRSEDUC 0.451931 0.0335255 13.48 5.73e-041 *** Mean dependent var 16.77115 Sum squared resid 598935.5 R-squared F(1, 7984) Log-likelihood S.D. dependent var 8.758696 S.E. of regression 8.661234 Adjusted R-squared 0.022131 P-value(F) 0.022254 181.7164 5.73е-41 -28571.28 Akaike criterion 57146.55 Schwarz criterion 57160.52 Hannan-Quinn 57151.33 Use the above findings to answer the following questions: A-Given the above estimated outcome, test to verify if the slope coefficient of YRSEDUC is significant. Use a two-sided p-value statistical approach, and show all the required steps. B-Based on your findings above, do you think the variable YRSEDUC is an important factor impacting EARN? Why or why not? (Statistical tables are attached if needed)