Management
TITLE
COURSE
INSTITUTION
NAME
DATE
Do you observe a linear relationship between the 2 variables?
Yes
Is FloorArea a significant predictor of AssessmentValue?
Yes. r2-value = 93.8% which shows that FloorArea can predict AssessmentValue (Knight, 2018; Kutner et al, 2005).
Do you observe a linear relationship between the 2 variables?
No
Is Age a significant predictor of AssessmentValue?
No. r2-value = 3.2% hence Age cant predict AssessmentValue.
p-value = 0.327 which is above significance level of 0.05 (Olive, 2017).
AssessmentValue vs. FloorArea, Offices, Entrances, and Age.
Overall fit r2? 95.3%
What is the adjusted r2? 94.6%
Which predictors are considered significant if we work with α=0.05?
FloorArea and Number of Offices in the building (Morrissey & Ruxton, 2018).
Which predictors can be eliminated? Age and Number of entrances
What is the final model if we only use FloorArea and Offices as predictors?
AssessedValue = (0.244 x FloorArea) + (80.946 x Offices)
What would be the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago?
AssessedValue = (0.244 x 3500) + (80.946 x 2) = 1015.88
Is this assessed value consistent with what appears in the database?
Yes
References
Knight, G. P. (2018). A survey of some important techniques and issues in multiple regression. In New methods in reading comprehension research (pp. 13-30). Routledge.
Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005). Applied linear statistical models (Vol. 5). New York: McGraw-Hill Irwin.
Morrissey, M. B., & Ruxton, G. D. (2018). Multiple regression is not multiple regressions: the meaning of multiple regression and the non-problem of collinearity.
Olive, D. J. (2017). Linear regression. Heidelberg: Springer.
TITLE
COURSE
INSTITUTION
NAME
DATE
Do you observe a linear relationship between the 2 variables?
Yes
Is FloorArea a significant predictor of AssessmentValue?
Yes. r2-value = 93.8% which shows that FloorArea can predict AssessmentValue (Knight, 2018; Kutner et al, 2005).
Do you observe a linear relationship between the 2 variables?
No
Is Age a significant predictor of AssessmentValue?
No. r2-value = 3.2% hence Age cant predict AssessmentValue.
p-value = 0.327 which is above significance level of 0.05 (Olive, 2017).
AssessmentValue vs. FloorArea, Offices, Entrances, and Age.
Overall fit r2? 95.3%
What is the adjusted r2? 94.6%
Which predictors are considered significant if we work with α=0.05?
FloorArea and Number of Offices in the building (Morrissey & Ruxton, 2018).
Which predictors can be eliminated? Age and Number of entrances
What is the final model if we only use FloorArea and Offices as predictors?
AssessedValue = (0.244 x FloorArea) + (80.946 x Offices)
What would be the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago?
AssessedValue = (0.244 x 3500) + (80.946 x 2) = 1015.88
Is this assessed value consistent with what appears in the database?
Yes
References
Knight, G. P. (2018). A survey of some important techniques and issues in multiple regression. In New methods in reading comprehension research (pp. 13-30). Routledge.
Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005). Applied linear statistical models (Vol. 5). New York: McGraw-Hill Irwin.
Morrissey, M. B., & Ruxton, G. D. (2018). Multiple regression is not multiple regressions: the meaning of multiple regression and the non-problem of collinearity.
Olive, D. J. (2017). Linear regression. Heidelberg: Springer.
