Page 12 - Regression Guideline

An"Example"of"SAVVI’s"Regression" Modeling"Steps"
"Sidebar:&What&is&staDsDcal®ression&and&why&is&it&called&linear?&
Linear"regression"is"a"staJsJcal"technique"that"models"the" relaJonship"between"one"(bivariate)"or"more"(mulJvariable)" predictor"variables"with"one"independent"variable"by"esJmaJng"a" linear"equaJon"based"on"observed"data."The"model"is"linear" because"it"assumes"either"a"constantly"increasing"(posiJve)"or" decreasing"(negaJve)"relaJonship"between"the"set"of"predictors" and"the"dependent"variable.""
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For"example,"in"a"linear"regression"model,"as"square"footage" increases,"the"sales"price"is"assumed"to"increase"at"a"constant"rate" as"in"our"earlier"example"where"sales"price"increased"$100"for"every" 1"foot"increase"in"square"feet."A"linear"relaJonship"is"usually"a"safe" assumpJon"for"most"applicaJons"of"regression"modeling"to" property"appraisal.""
There"could"be"rare"instances"such"as"at"the"high"end"of"the"market,"however,"where"increasing" square"footage"a^er"a"certain"point"will"have"a"diminishing"effect"on"sales"price;"beyond"a"certain" size,"people"might"not"be"willing"to"pay"as"much"for"each"addiJonal"square"foot"of"living"space." This"results"in"what"is"called"a"“curvilinear"effect”,"in"which"case"addiJonal"terms"must"be"added"to" the"regression"model"to"capture"the"diminishing"returns"for"increasing"square"footage."A"linear" regression"model"will"predict"well"up"to"the"point"of"diminishing"returns."A^er"that"point,"the" model"will"sJll"be"predicJve"but"less"accurate"without"adjusJng"for"the"curvilinear"effect."As" indicated,"in"the"large"majority"of"circumstances"in"appraising,"the"linear"model"works"well"and"is" very"accurate."
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