Smith is studying the relationship between length (X) and weight (Y) of infants. Please help him fit an exponential growth model to find the relationship between length and weight. Write down the model and explain how to fit the model (i.e., how to estimate regression coefficients) and what the intercept is for the relationship between X and Y (in symbolic form).

You estimate a regression equation that estimates individuals’ yearly income as a function of age (measured in years), years of education, and their score on a standardized intelligence exam (IQ test). The estimated coefficients are:      I = 26.3 + 4.21*Age + 7.21*Education + .23 * IQ Where I is income measured in thousands of dollars.         Based on the regression results, how much more should an individual earn after attending graduate school for two years? Explain your reasoning.

What needs to change in an overall problem if one wants to use linear regression?

biologist was recording various temperatures (in degrees Celsius) and predicting the amount of glucose produced by a plant (in milligrams). Suppose the linear equation was the following: ?̂ = 12.7 − 0.223? a) Interpret the slope of the regression line.

Height Weight GPA Study TV Computer FamilySz Floors stairs friends female Acctg Mgmt Mktg Fin IntBus Other 67 138 4 6 2 1. 2 26 6. 1 73 175 3.47 5 4 26 1 62 112 4 6 2 1. 4 34 3 1 1. 64.5 122 3.5 3.4 1. 3 47 4 1 1. 69 135 4 4 2 4 13 1. 61 129 3.8 4 2 3 5 17 1. 1. 64 135 3.4 3 2 5 1. 1 1. 68 150 4 10 1 4 2 31 4 1 1 70 130 3.8 4 1 2 4 2 26 8. 1 65 172 3.6 2.5 1.5 0.5 4 2 26 8. 1 74 235 2.6 1. 1. 1. 4 3 52 1. 69 150 3 2 3 3 4 3 26 1. 72 152 2.8 2.5 0.5 3 5 3 30 10 1. 73 155 3 1. 2 4 2 26 1 74 170 3.75 1.5 1.5 2 15 5 1. 68 150 3 2.5 1. 4 3 26 10 1 63 115 2.5 3 2.5 3 2 13 8 1. 1 71 180 2.1 1 3 3 4 13 10 1 72 167 2.7 2. 4 4 2 18 3 72 180 3.8 2 1.5 0.5 1. 300 68.575 152.6 3.341 3.395 1.55 1.75 4.1 2.2 38.25 5.8 s= 4.146257 28.65842 0.584798 2.137257 0.759155 1.409554 0.640723 0.695852 62.7215 2.587419 ------ ---- ----- ----- ----- ----- ---- ----- ----- ----- ----- ------ ----- ---- ---- --

X₁ is the The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -51.2 +0.4x₁ + 4.8x2, where tree's height (in feet) and x₂ is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ = 73, x₂ = 8.8 (b) x₁ = 67, x₂ = 11.5 (c) x₁ = 85, x₂ = 17.6 (d) x₁ = 92, x₂ = 20.8 cubic feet. (a) The predicted volume is (Round to one decimal place as needed.) (b) The predicted volume is cubic feet. (Round to one decimal place as needed.) (c) The predicted volume is cubic feet. (Round to one decimal place as needed.) (d) The predicted volume is cubic feet. (Round to one decimal place as needed.) Next

A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.

What are the interpretations of the Y intercept and the slopes in a multiple regression model?

The volume​ (in cubic​ feet) of a black cherry tree can be modeled by the equation y=−50.8+0.3x1+5.1x2​, where x1 is the​ tree's height​ (in feet) and x2 is the​ tree's diameter​ (in inches). Use the multiple regression equation to predict the​ y-values for the values of the independent variables.

How should I draw this linear regression graph for this model? Thanks.