In a regression analysis involving 30 observations, the following estimated regression equation was obtained. ŷ = 18.7 + 3.7x₂ - 2.3x₂ + 7.6x3 + 2.9x4 (a) Interpret b, in this estimated regression equation. O b₁ = 7.6 is an estimate of the change in y corresponding to a 1 unit change in x3 when X₁, X₂, and x4 are held constant. = 2.9 is an estimate of the change in y corresponding to a 1 unit change in x4 when X₁, X₂, and x3 are held constant. Ob₁ = Ob₁ = 3.7 is an estimate of the change in y corresponding to a 1 unit change in x₁ when X₂, X3, and x4 are held constant. O b₁ = -2.3 is an estimate of the change in y corresponding to a 1 unit change in x₁ when X2, X3, and x4 are held constant. Ob₁ = = 3.7 is an estimate of the change in y corresponding to a 1 unit change in x₂ when X₁, X3, and x4 are held constant. Interpret b₂ in this estimated regression equation. O b₂ = -2.3 is an estimate of the change in y corresponding to a 1 unit change in x₂ when X₁, X3, and x4 are held constant. O b₂ = 2.9 is an estimate of the change in y corresponding to a 1 unit change in X4 when X₁, X₂, and x3 are held constant. O b₂ = -2.3 is an estimate of the change in y corresponding to a 1 unit change in x, when X₂ X3, and x4 are held constant. Ob₂= = 7.6 is an estimate of the change in y corresponding to a 1 unit change in x3 when X₁, X₂, and x4 are held constant. O b₂ = 3.7 is an estimate of the change in y corresponding to a 1 unit change in x₁ when X₂, X3, and x4 are held constant. Interpret b in this estimated regression equation. O b3 = -2.9 is an estimate of the change in y corresponding to a 1 unit change in X4 when X₁, X₂, and x3 are held constant. O b3 = 7.6 is an estimate of the change in y corresponding to a 1 unit change in x₂ when X₁, X3, and x4 are held constant. O b3 = 3.7 is an estimate of the change in y corresponding to a 1 unit change in x3 when X₁, X₂, and x4 are held constant. O b3 = 7.6 is an estimate of the change in y corresponding to a 1 unit change in x3 when X₁, X₂, and x4 are held constant. O b3 = -2.3 is an estimate of the change in y corresponding to a 1 unit change in x₁ when X₂, X3, and X4 are held constant. Interpret b in this estimated regression equation. O b4 = -2.3 is an estimate of the change in y corresponding to a 1 unit change in x₂ when X₁, X3, and x4 are held constant. O b4 = 7.6 is an estimate of the change in y corresponding to a 1 unit change in x₂ when X₁, X3, and x3 are held constant. O b4 = 2.9 is an estimate of the change in y corresponding to a 1 unit change in X3 when X₁, X₂, and x4 are held constant. O b4 = 3.7 is an estimate of the change in y corresponding to a 1 unit change in x4 when X₁, X₂, and x3 are held constant. O b4 = 2.9 is an estimate of the change in y corresponding to a 1 unit change in x4 when X₁, X₂, and x3 are held constant. (b) Predict y when x₁ = 10, x₂ = 5, x3 = 1, and x4 = 2.

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: ý=ax+b a=-0.873 b=26.236 r2=0.527076 r=-0.726 Use this to predict the number of situps a person who watches 11 hours of TV can do (to one decimal place)

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.113 b=31.204 r2=0.866761 r=-0.931 Use this to predict the number of situps a person who watches 9.5 hours of TV can do (to one decimal place)

The accompanying data are the length​ (in centimeters) and girths​ (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given​ x-values, if meaningful. If the​ x-value is not meaningful to predict the value of​ y, explain why not. ​(a) x=140 cm ​(b) x=172 cm ​(c) x=164 cm ​(d) x=158 cm Length, x    Girth, y138    106168    130153    116144    105159    126158    119124    103137    103154    121148    111147    106145    110 The equation of the regression line is y=____x + ___