L TABLE 14-3 Afinanciai analyst wanted to examine the relationship between salary (in $1,000] and 4 variables: age [X1 = Age). experience in the

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L—TABLE 14-3 Afinanciai analyst wanted to examine the relationship between salary (in $1,000] and 4 variables: age [X1 = Age). experience in the field [X2 = Exper}. number of degrees (X3 = Degrees], and number of previous jobsin the field (X4 = Prevjobs). He took a sample of 20 employees and obtained the following Microsoft Boel output: SUMMARY OUTPUTRegression StatisticsMultiple R 0 992 R Square 0 984Ad]usted R Square 0 979Standard Error 2.26?43 Observations 20ANOVA(if SS MS F 5181‘thRegression 4 460983164 115245791 224 160 0 0001Residual 15 27.11836 5.14122Total 19 4686.95000Coeff StdEr’mr E Stat P—ww‘mIntercept 79 611198 2 T?988638 73.45? 0.0035Age 1.327695 011491930 11553 0.0001Exper 70106705 014265559 70.?48 0.4660Degrees 7.311332 0 80324187 9102 0.0001Prevjobs —0 504168 0447?15?3 —1.126 0.27?8 True or False: Referring to Table 144, the analgst wants to use a ttest to test for the significance of the coefficient ofXa. At a level of significance of 0.01 , the department head would decide that 53 a U.("V True-" False

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