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You choose - Assignment Example Correlation analysis, regression analysis, and student t-test for difference in means across factors are possible tools for analyzing effect of the factors on sales price. Correlation analysis results suggest a moderate negative relationship between price and floor, a moderate positive relationship between price and distance, and strong positive relationship between price and view. End and furnish have weak and negative relationships with price. Appendix 2 shows the results. Regression analysis for the relationship between price and the other variables, as independent variables, identifies a significant relationship (p=2.42*10-23, F= 39.69) and the model is reliable. Appendix 3 shows the results. View of the beach is significant (p= 4.3*10-20, t= 1.92) and apartments with view of the sea have higher prices (mean= 22021.3) than those without view (mean= 18105). Appendix 4 shows the results. Apartments with their views partially blocked have lower prices (mean=18714.3) than those that are not blocked (mean= 20177.7) but the difference is not significant (p= 0.26, t= 1.97). Appendix 5 shows the results. Price difference between apartments with furniture and those without is however minimal (means= 20104.2, 20141.6 respectively) and the difference is not significant (p= 0.99, t= 1.97). Appendix 6 shows the results. Appendix 7 shows table of coefficients for regression analysis results for the relationship between price and the independent variables. The results shows that only furniture is not significant to price (p= 0.24, t= 1.19) and the following is the model. The model omits furniture because it is not significant. It is important to note that while end is not significant when considered separately, it is significant when investigated with other variables and interaction effects could explain this. Coefficients of the regression analysis