This assignment provides an opportunity to develop, evaluate, and apply bivariate and multivariate linear regression models.

Assignment Content

  1. Purpose 
    This provision provides an convenience to amplify, evaluate, and dedicate bivariate and multivariate direct retrogradation patterns.


    Resources: Microsoft Excel®, DAT565_v3_Wk5_Data_File


    Instructions:
    The Excel finish for this provision contains a basisbase after a while counsel about the tax tribute esteem assigned to medical business-post fabrics in a city. The aftercited is a roll of the mutables in the basisbase:
    • FloorArea: balance feet of sole space
    • Offices: estimate of business-posts in the fabric
    • Entrances: estimate of customer entrances
    • Age: age of the fabric (years)
    • AssessedValue: tax tribute esteem (thousands of dollars)
    • Use the basis to form a pattern that predicts the tax tribute esteem assigned to medical business-post fabrics after a while unfair characteristics.

    • Construct a strew devise in Excel after a while FloorArea as the fractions mutable and AssessmentValue as the relative mutable. Insert the bivariate direct retrogradation equation and r^2 in your graph. Do you watch a direct kindred betwixt the 2 mutables?
    • Use Excel’s Resolution ToolPak to guide a retrogradation resolution of FloorArea and AssessmentValue. Is FloorArea a indicative predictor of AssessmentValue?
    • Construct a strew devise in Excel after a while Age as the fractions mutable and AssessmentValue as the relative mutable. Insert the bivariate direct retrogradation equation and r^2 in your graph. Do you watch a direct kindred betwixt the 2 mutables?
    • Use Excel’s Resolution ToolPak to guide a retrogradation resolution of Age and Tribute Value. Is Age a indicative predictor of AssessmentValue?
    • Construct a multiple retrogradation pattern.
    • Use Excel’s Resolution ToolPak to guide a retrogradation resolution after a while AssessmentValue as the relative mutable and FloorAreaOfficesEntrances, and Age as fractions mutables. What is the overall fit r^2? What is the adjusted r^2?
    • Which predictors are considered indicative if we is-sue after a while α=0.05? Which predictors can be eliminated?
    • What is the latest pattern if we merely use FloorArea and Offices as predictors?
    • Suppose our latest pattern is:
    • AssessedValue = 115.9 + 0.26 x FloorArea + 78.34 x Offices
    • What would be the assessed esteem of a medical business-post fabric after a while a sole area of 3500 sq. ft., 2 business-posts, that was built 15 years ago? Is this assessed esteem accordant after a while what appears in the basisbase?
    • Submit your provision. 
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