The polynomial regression model of degree r is given by Yį = B₁ + B₁X₁ + ß₂X² + ··· + ß₂X{ + U₂. (a) Interpret the coefficient 3₁ in a linear regression (r = 1): Y = 3o+ BiXi t and in a quadratic regression (r = 2): Y₁ = B₁ + B₁X₁ + ß₂X² + U₂.
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- Use the linear regression model yˆ=−21.9x+927.93 to predict the y-value for x=37.Solve bThe volume (in cubic feet) of a black cherry tree can be modeled by the equation y=−51.9+0.3x1+4.9x2, 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.
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- A study investigating the relationship between a country's annual gross domestic product x (in trillions of dollars) and carbon dioxide emissions y(in millions of metric tons) yielded r = 0.87, se = 141.9 , and the regression equation y-hat = 199.5x + 56.0. For each additional trillion dollars in %3D gross domestic product, carbon dioxide emissions increases by about 0.87 million metric tons, on average increases by about 199.5 million metric tons, on average changes by an amount that cannot be determined from the information given O increases by about 141.9 million metric tons, on average increases by about 56.0 million metric tons, on averageA particular article used a multiple regression model to relate y = yield of hops to x₁ = mean temperature (°C) between date of coming into hop and date of picking and x₂ = mean percentage of sunshine during the same period. The model equation proposed is the following. y = 415.116.6x₁4.50x2+e (a) Suppose that this equation does indeed describe the true relationship. What mean yield corresponds to a temperature of 20 and a sunshine percentage of 39? (b) What is the mean yield when the mean temperature and percentage of sunshine are 19.1 and 42, respectively? You may need to use the appropriate table in Appendix A to answer this question.An oceanographer measured the length, in meters, of a deepwater wave and its speed, in meters per second. The results are shown in the following table. (a) Find the equation of a linear regression line for the data where wave length is the independent variable, x, and speed is the dependent variable. (Round your numerical values to two decimal places.) y= ? (b) Using the equation from part (a), estimate the speed (in meters per second) of a wave that is 200 m long. (Round your answer to one decimal place.) ? m/s