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(To obtain a scatter plot in Gretl, → View → graph specified vars → XY Scatter → X-axis variables (sqrft) →Y-axis variable (price) and ok.)
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Is there significant evidence that an increase in the total living area by one square meter increases the price of a small house by less than 500, on average? Test this at the 1% significance level and clearly state your conclusion. Copy and paste your regression output.
Restore the full sample range and answer the followings. (To restore full sample range in Gretl select 'sample' 'restore full range'.)
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(Note: a summary report should contain the estimated regression equation, standard errors, t ratios, the number of observations, goodness of fit statistic, and the F value for the overall significance test. See the example below.)
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Figure 2: Linear Regression Analysis
= + + .
From figure 2, the regression equation will be:
= 29644.3 + 498.169 + 30196.01
Choice of Statistics
As population variance is not known and the sample size is large, t statistics is preferred in this case.
Framing a Hypothesis
Ho: dprice/dsqmt >= 500
H1: dprice/dsqmt < 500