DAT_565_Week_5.docx DAT/565 Regression Modeling DAT/565 University of Phoenix Regress

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DAT_565_Week_5.docx DAT/565 Regression Modeling DAT/565 University of Phoenix Regression Modeling The first scatter plot will be analyzing two variables, which are Assessed Value and Floor Area... . From the scatter graph above, we can see a positive relationship between the two variables since there is a rising regression line. From the summary output above, we can conclude that the floor area is a significant predictor of Assessment value. The second graph represents a comparison of two variables, which are Assessed value and Age. From the scatter plot above, there are many plots in every section; hence, we can conclude no relationship between the two variables. From the summary output, we can conclude that Age is not a significant predictor of assessment value. Regression analysis with Assessed Value and Floor Area, Offices, Entrances, and Age From this summary output, we can determine the value of R Square as 0.9530. The value of the adjusted R square is 0.9461. Floor area and office are the predictors that are considered significant when working with the value of alpha as 0.05; this is because their p-value is below 0.05. Also, the predictors which can be eliminated are Age and Entrance because their p-value is above 0.05. Final model Assessed Value = 115.9 + 0.26 × Floor Area + 78.4 × Offices We can also determine the formula of the assessed value of a medical office building consisting of a floor area of 3,500 square feet and two offices constructed 15 years ago. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .. .. . . . . . . . . . . . . . . . . . .. . . . . [Show More]

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