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The adjusted R2 and unadjusted R2 are identical only when the unadjusted R2 is equal
to 1
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The way to determine whether a group of explanatory variables exerts significant
influence on the dependent variable is to see if any of the explanatory variables has a
significant t statistic; if not, they are statistically insignificant as a group
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When R2 = 1, F = 0, and when R2 = 0, F = infinite
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When the d.f. exceed 120, the 5% critical t value (two-tail) and the 5%
critical Z (standard normal) value are identical, namely, 1.96.
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In the model, if X2 and X3 are negatively correlated in the sample and, omitting X3 from
the model will bias b2 downward [i.e., ] where b2 is the slope coefficient in the
regression of Y on X2 alone
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When we say that an estimated regression coefficient is statistically significant, we mean
that it is statistically different from 1.
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To compute a critical t value, we need to know only the d.f.
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By the overall significance of a multiple regression we mean the statistical significance of
any single variable included in the model.
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In a log-log model the dependent and all explanatory variables are not in the logarithmic
form
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Elasticity coefficient is the unit change in the value of one variable for a (small) unit
change in the value of another variable. For the log-log model, the slope coefficient of
an explanatory variable gives a indirect estimate of the elasticity coefficient of the
dependent variable with respect to the given explanatory variable
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