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2. A linear probability model (LPM) has been estimated using Ordinary Least Squares (OLS) with a sample of N = 500 observations, yielding the following results: $Y_i = 12.4 + 3.4X_{1,i} - 0.2X_{2,i} + \hat{u}_i$ (23) (3.2) (-0.9) Knowing that the values in parentheses correspond to the individual significance statistics (t-ratios) of the estimated parameters, then it can be stated that: a) The constant and the parameter of variable $X_{1,i}$ are statistically significant at a 5% significance level. b) All estimated parameters are statistically significant at a 5% significance level. c) Only the parameter of variable $X_{2,i}$ is statistically significant at a 5% significance level. d) Based on the available information, it cannot be determined which estimated parameters are statistically significant.

          2. A linear probability model (LPM) has been estimated using Ordinary Least Squares
(OLS) with a sample of N = 500 observations, yielding the following results:
$Y_i = 12.4 + 3.4X_{1,i} - 0.2X_{2,i} + \hat{u}_i$
(23) (3.2) (-0.9)
Knowing that the values in parentheses correspond to the individual significance
statistics (t-ratios) of the estimated parameters, then it can be stated that:
a) The constant and the parameter of variable $X_{1,i}$ are statistically significant at a 5%
significance level.
b) All estimated parameters are statistically significant at a 5% significance level.
c) Only the parameter of variable $X_{2,i}$ is statistically significant at a 5% significance
level.
d) Based on the available information, it cannot be determined which estimated
parameters are statistically significant.

2. A linear probability model (LPM) has been estimated using Ordinary Least Squares
(OLS) with a sample of N = 500 observations, yielding the following results:
Yi = 12.4 + 3.4X1,i - 0.2X2,i + ûi
(23) (3.2) (-0.9)
Knowing that the values in parentheses correspond to the individual significance
statistics (t-ratios) of the estimated parameters, then it can be stated that:
a) The constant and the parameter of variable X1,i are statistically significant at a 5%
significance level.
b) All estimated parameters are statistically significant at a 5% significance level.
c) Only the parameter of variable X2,i is statistically significant at a 5% significance
level.
d) Based on the available information, it cannot be determined which estimated
parameters are statistically significant.

Added by Samantha S.

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