The questions below are based on a dataset containing the characteristics of 5,407 households. In particular, we will use the following variables: - size: home size, measured in square feet. - hhinc:...


 Consider the results in Table 2. Compute the 99% confidence interval for hhinc


The questions below are based on a dataset containing the characteristics of 5,407<br>households. In particular, we will use the following variables:<br>- size: home size, measured in square feet.<br>- hhinc: annual household net income, measured in euros.<br>- owner. dummy variable equal to 1 if the living space is owned, and 0 if the living<br>space is rented.<br>- hhsize1: dummy variable equal to 1 if the number of household's members is 1 or<br>2, and 0 otherwise.<br>hhsize2: dummy variable equal to 1 if the number of household's members is 3 or<br>4, and 0 otherwise.<br>hhsize3: dummy variable equal to 1 if the number of household's members is 5 or<br>above 5, and 0 otherwise.<br>- edu: education level of household's members.<br>The Appendix contains tables with the critical values of the standard normal distribution and<br>the F distribution.<br>

Extracted text: The questions below are based on a dataset containing the characteristics of 5,407 households. In particular, we will use the following variables: - size: home size, measured in square feet. - hhinc: annual household net income, measured in euros. - owner. dummy variable equal to 1 if the living space is owned, and 0 if the living space is rented. - hhsize1: dummy variable equal to 1 if the number of household's members is 1 or 2, and 0 otherwise. hhsize2: dummy variable equal to 1 if the number of household's members is 3 or 4, and 0 otherwise. hhsize3: dummy variable equal to 1 if the number of household's members is 5 or above 5, and 0 otherwise. - edu: education level of household's members. The Appendix contains tables with the critical values of the standard normal distribution and the F distribution.
Table 2<br>· regress size hhinc, robust<br>Linear regression<br>Number of obs<br>5,407<br>F(1, 5405)<br>134.25<br>Prob > F<br>0.0000<br>R-squared<br>0.2299<br>Root MSE<br>403.86<br>Robust<br>size<br>Coefficient std. err.<br>t<br>P>|t|<br>[95% conf. intervall<br>hhinc<br>.0082545<br>.0007124<br>11.59<br>„cons<br>800.9835<br>25.72644<br>31.13<br>

Extracted text: Table 2 · regress size hhinc, robust Linear regression Number of obs 5,407 F(1, 5405) 134.25 Prob > F 0.0000 R-squared 0.2299 Root MSE 403.86 Robust size Coefficient std. err. t P>|t| [95% conf. intervall hhinc .0082545 .0007124 11.59 „cons 800.9835 25.72644 31.13

Jun 11, 2022
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