# Introduction. Before Moving Into A New Neighborhood, There

704 WordsMay 2, 20173 Pages
Introduction Before moving into a new neighborhood, there are many indexes people need to take into consideration, for instance, the crime rates, the quality of the educational institutions in the neighborhood as well as other neighborhood welfares. It is common for people who have children to move to districts with great educational services. On the contrary, people who do not have children will move out of these neighborhoods to avoid additional fees. Sometimes. These factors which affect people decisions to stay in or move out of the neighborhood interest me. This project will study the correlations between the population of Denver neighborhoods and 6 possible factors. The dataset was gathered from 45 Denver neighborhoods. And I will…show more content…
Then I run a Fit Regression Model with x3, x6 and x7. Then I test the significance of the regression line. To test the significance of the coefficients: H0: βk = 0 (k=3, 6, 7); H1: at least one of these coefficients does not equal to 0. F= [∑ (ŷi- ȳ) /p] / σ^2 = MSR/MSE = 3.56 with p-value = 0.02 < 0.05; σ^2 = ∑ (Yi - ŷi) ^2 / (n-p-1) = 426.61. The F value is statistically significant. Therefore, we have the sufficient evidences reject the null hypothesis. To test the significance of the intercept:H0: β0=0; H1: β0≠0. t (n-4) = ^β0- β0 / SE (^β0) = 2.89; p-value = 0.006 <0.05. The t-score is statistically significant. Therefore, we have sufficient evidence to reject the null hypothesis. To test the significance of other coefficients. H0: βk=0; H1: βk≠0. K= (3,6,7) t (n-4) = ^β3- β3 / SE (^β3) = (0.0631-0)/ 2.05 = 2.89 with p-value = 0.308; t (n-4) = ^β6- β6 / SE (^β6) = (-0.01325 - 0)/ 0.00502= -2.64 with p-value = 0.0128*; t (n-4) = ^β7- β7 / SE (^β7) = (-0.0605 -0)/ 0.0298= -2.03 with p-value= 0.049* The t-score is statistically significant for β6 and β7. Therefore, we have sufficient evidence to reject the null hypothesis for β6 and β7. However, the t-score is not statistically significant for β3. Therefore, we fail to reject the null hypothesis of β3. Then I run 4 residual plots for the regression. From the normal probability plot, the residuals fall along the