Consider the following estimated regression model: Ý = 1.46 – 2.4 X + 0.75X2¡,i = 1, ... ,25, %3D %3D (1.32) (0.6) (0.25) where standard errors appear in parentheses. Then, for the following hypothesis test run with a t-test: Ho: B2 = 0.25 HA: B2 + 0.25, %3D the t-statistic equals 4 O the t-statistic equals 3 the t-statistic equals 2 O the t-statistic equals 1 O None of the above statements are true.

A First Course in Probability (10th Edition)
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ISBN:9780134753119
Author:Sheldon Ross
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Chapter1: Combinatorial Analysis
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Consider the following estimated regression model:
Ý = 1.46 – 2.4 Xi + 0.75X2i,i = 1, ... ,25,
%3D
%3D
(1.32)
(0.6)
(0.25)
where standard errors appear in parentheses. Then, for the following hypothesis test run with at-test:
Ho: B2 = 0.25
HA: B2 + 0.25,
the t-statistic equals 4
O the t-statistic equals 3
the t-statistic equals 2
O the t-statistic equals 1
O None of the above statements are true.
Transcribed Image Text:Consider the following estimated regression model: Ý = 1.46 – 2.4 Xi + 0.75X2i,i = 1, ... ,25, %3D %3D (1.32) (0.6) (0.25) where standard errors appear in parentheses. Then, for the following hypothesis test run with at-test: Ho: B2 = 0.25 HA: B2 + 0.25, the t-statistic equals 4 O the t-statistic equals 3 the t-statistic equals 2 O the t-statistic equals 1 O None of the above statements are true.
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