Suppose you are estimating parameters of the following regression model:
Ŷt = 9941 + 0.25 X2t+ 15125 X3t
(6114) (0.121) (7349)
R2= 0.87, RSS = 10310
complete question:Suppose you are estimating parameters of the following regression model:
Ŷt = 9941 + 0.25 X2t+ 15125 X3t
(6114) (0.121) (7349)
R2= 0.87, RSS = 10310
(The figures in parentheses are the estimated standard errors. RSS are residual sum of squares.)(A) Using t-tests show whether individual coefficients are significantly different from zero at 5%
level of significance.(B) Test whether the coefficient of X2 is significantly different from 1 at 5% level ofsignificance.
solution
"A) \\\\\n\nH0:\u03b2_0=0\\space vs\\space H1: \u03b2_0\u22600\\\\T=\\frac{\u03b2_0\u02c6\u2212\u03b2_0}{S.D.(\u03b2_0)}\\\\Under\\space Null\\space hypothesis\\\\T= \\frac{9941}{6114} =1.626\\\\H0:\u03b2_1=0\\space vs\\space H1: \u03b2_1\u22600\\\\T=\\frac{\\bar{\u03b2_1}\u2212\u03b2_1}{S.D.(\u03b2_1)}\\\\Under\\space Null\\space hypothesis\\\\T= \\frac{0.25}{0.121} =2.066\\\\ H0:\u03b2_2=0 \\space vs \\space H1: \u03b2_2\u22600\\\\T=\\frac{\\bar{\u03b2_2}\u2212\u03b2_2}{S.D.(\u03b2_2)}\\\\Under\\space Null \\space hypothesis\\\\T= \\frac{15125}{7349} =2.058"
"H0:\u03b2_1=1 \\space vs \\space H1: \u03b2_1\u22601\\\\T=\\frac{\\bar{\u03b2_1}\u2212\u03b2_1}{S.D.(\u03b2_1)}\\\\Under\\space Null\\space hypothesis\\\\T=\\frac{ 0.25\u22121}{0.121} =\u22126.19"
If T critical is less than the calculated value of T then we reject null hypothesis and conclude that there is significance of thecoefficient '
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