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True or False problems on regression models.

State with brief reasons whether the following statements are true, false, or uncertain.

a. OLS is an estimating procedure which minimizes the sum of the errors squared, ∑ui2.

b. The assumptions made by the classical linear regression model (CLRM) are not necessary to compute OLS estimators.

c. The theoretical justification for OLS is provided by the Gauss-Markov theorem.

d. In the two-variable, PRF, b2 is likely to be a more accurate estimate of B2 if the disturbances ui follow the normal distribution.

e. The OLS estimator's b1 and b2 each follow the normal distribution only if ui follows the normal distribution.

f. r2 is the ratio of TSS/ESS.

g. For a given alpha and d.f., if the computed t exceeds the critical t value, we should accept the null hypothesis.

h. The coefficient of correlation, r has the same sign as the slope coefficient b2

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