Regression AnalysisYou are a newly hired research assistant at RLJ Consulting Services and on your first dayat work your boss asks you to review a research study done by your recently firedpredecessor. The aim of the project was to determine where houses were more valuable;Stockton, CA or Baton Rouge, LA. Your predecessor decided that the best approach toanswering this question was to test whether the mean house price in Stockton was largerthan the mean house price in Baton Rouge. You predecessor had taken an econometricsclass and realized that this is equivalent to estimating the following regression:i i i 0 1 price Stockton ? ? ? ? ? ?using the ordinary least squares estimator with homoscedastic errors. The results of thisregression are reported in Table 1 below:Table 1: Regression Results for Testing Differences in HousePrices between Stockton, CA and Baton Rouge, LADependent Variable: PRICESample: 1 1960Included observations: 1960Variable Coefficient Std. Error t-Statistic Prob.C 154863.2 2977.937 52.00351 0.0000STOCKTON -42052.37 4444.288 -9.462116 0.0000R-squared 0.043727 Mean dependent var 135982.5Adjusted R-squared 0.043238 S.D. dependent var 100051.9S.E. of regression 97864.99 Akaike info criterion 25.82159Sum squared resid 1.88E+13 Schwarz criterion 25.82728Log likelihood -25303.15 Hannan-Quinn criter. 25.82368F-statistic 89.53163 Durbin-Watson stat 1.347164Prob(F-statistic) 0.000000The results suggest that Stockton house prices are, on average, $42,052.37 lower thanBaton Rouge, LA and the 95% confidence interval for the difference in means is?? ? $50,768.40, $34,738.70?Your boss, Dr Snow, saw these results and said that these results do not make sense giventhat house prices in California are high relative to the rest of the country.Your task is to redo this analysis and, this time, get it right!

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