I was wondering specifically about part D and how to interpret my findings. Q5. This regression analysis on the number of hours spent emailing for work (EMAILHRS) is thedependent variable and years of education (EDUC) is the independent variable. Dang. Once again, STATAforgot to report key values (or someone deleted them, hmmm). Using what is left, answer the questionsbelow.regress EMAILHR EDUC, level (99)Source |Model | 1474.89013Residual | 2087917.95Total | 2089392.84EMAILHR1.2.3.4.5.SSEDUC | .4443524cons | 3.190798H1Coef.Ho: Bk.ко 2Вк doesn'tBK=0b) Fill in the missing variables.dfStd. Err.55060347.833696MS2831833 2263.69755737.45tNumber of obsF(,)Prob > FR-squaredAdj R-squaredRoot MSEP>|t|0.81 0.4200.41 0.684a) State the hypothesis in words and mathematical notation. State the alpha reflected in the STATAoutput.:|| ||-.9768499-17.02932こMSE2,512. 54.d) Make a decision about your hypothesis and state it fully.834[99% Conf. Interval]1.86555523.410920.0007-0.000447.587df1 =df2=N-K-1=831Means Squares Regression = 147489013/2 = 737.45Mean Squares Residual = 2087917.95/831= √2,512.54Obtained F-value =MSR737.450.290 lat least one of the coefficients in 10)

Given that, Dependent variable (y) = the number of hours spent emailing for work. Independent…

a) State the hypothesis in words and mathematical notation. State the alpha reflected in the STATA output. H₁: B₁ doesn't = 0 (at least one of the coefficients inta 1 H₂: BK = 0 b) Fill in the missing variables. 1. 2. 3. 4. 5. df1 = ког df2= N-K-1 = 831 Means Squares Regression = 147489013/2 Mean Squares Residual = 2687917.95/831= Obtained F-value = 737.45 MSR 737.45 = 2,512.54 0.29 = > MSE 2,5₁2. 54. d) Make a decision about your hypothesis and state it fully.