Use the following information to answer the questions follow. A regression model has been estimated using the OLS to show the following relationship. Y = Bo + BX + B2X2 + B3X3 + u (Model 1) The OLS estimation output is given below. Some values in the Gretl output have been deleted deliberately. Model 1: OLS, using observations 1-30 Dependent variable: Y const X1 X2 X3 coefficient -0.0682414 0.145077 -1.77528 -0.224399 R-squared F(3, 26) Log-likelihood std. error Mean dependent var -3.663533 Sum squared resid 44.82499 ???????? ???????? -48.59168 110.7882 Schwarz criterion 0.481660 0.222371 0.163884 0.142149 t-ratio p-value ?????? ?????? ?????? ?????? ?????? 0.1265 S.D. dependent var S.E. of regression 0.8884 0.5199 Adjusted R-squared P-value (F) Akaike criterion Hannan-Quinn 2.946952 1.313026 ???????? 6.88e-10 105.1834 106.9764 1. What is the observed value of the t statistic for the test Ho: B = 0 against H B0? (3 d.p.). 2. What is the 1% critical value for the test for the test Ho: B = 0 against H : B # 0? (3 d.p.). 3. Would you reject the null hypothesis Ho : B = 0 against H : 0? OThe absolute value of test statistic is larger than 5% critical value, therefore do not reject Ho OThe absolute value of the test statistic is smaller than the 1% critical value, therefore do not reject Ho OThe p-value is smaller than 1%, therefore do not reject Ho OThe p-value is larger than 1%, therefore reject Ho OThe absolute value of test statistic is larger than 1% critical value, therefore reject Ho 4. Does X is an important variable in explaining variations in Y? OYes, the X is an important variable at 1% significance level but not at 5% significance level. OX is NOT an important variable at 5% significance level. ONone of the answers is correct. OYes X is an important variable at 1% significance level. OX is NOT an important variable at 10% significance level.