Equation for the best Straight line Yi=b0+b,X 1636.415+1.487X From Excel printout Coefficien ts In te rce pt 1636.414726 x Varia ble.486633657
Equation for the Best Straight Line i i i . . X Y b b X 1636 415 1 487 0 1 = + = + From Excel Printout: C o e ffic ie n ts I n te r c e p t 1 6 3 6 . 4 1 4 7 2 6 X V a r i a b l e 1 1 . 4 8 6 6 3 3 6 5 7
Graph of the best straight Line 12000 10000 8000 0 6000 4000 Y=1636.415+1.487X 2000 0 1000 200030004000 5000 6000 square Feet
Graph of the Best Straight Line 0 2000 4000 6000 8000 10000 12000 0 1000 2000 3000 4000 5000 6000 S q u a re F e e t Annual Sales ($000)
Interpreting the Results Y1=1636.415+1.487X The slope of 1.487 means for each increase of one unit in x the y is estimated to increase 1. 487units For each increase of 1 square foot in the size of the store, the model predicts that the expected annual sales are estimated to increase by $1487
Interpreting the Results Yi = 1636.415 +1.487Xi The slope of 1.487 means for each increase of one unit in X, the Y is estimated to increase 1.487units. For each increase of 1 square foot in the size of the store, the model predicts that the expected annual sales are estimated to increase by $1487.
Measures of variation: The Sum of squares变异平方和 SSTE Total Sum of Squares .measures the variation of the Y values around their mean y SSR= Regression Sum of Squares explained variation attributable to the relationship between X and y SSE= Error Sum of Squares variation attributable to factors other than the relationship between X andY
Measures of Variation: The Sum of Squares变异平方和 SST = Total Sum of Squares •measures the variation of the Yi values around their mean Y SSR = Regression Sum of Squares •explained variation attributable to the relationship between X and Y SSE = Error Sum of Squares •variation attributable to factors other than the relationship between X and Y _