Suppose we fit a regression line t o predict the shelf life of an apple based on its weight. For a particular apple, we predict the shelf life to be 4.6 d ays. The apple ’s residual is −0.6 days. Did we over- or under-estimate the shelf-life of the apple? Explain your reasoning

Table 3 gives the market value of a luxury sedan (in dollars) xyears after its purchase. Find an exponential regression model of the form y= ab* for this data set. Estimate the purchase price of the sedan. Estimate the value of the sedan 10 years after its purchase. Round answers to the nearest dollar. TABLE 3 Value ($) 1 23,125 19,050 3 15,625 11,875 5 9,450 6 7,125 2.

You decide to add a second independent variable to your regression. Male is a dummy variable that equals 1 if the individual is male and 0 otherwise. Your regression results are now:   wage = 3.071    +    0.289 × Years of Schooling + 1.28 × Male (0.143)        (0.0168)                                   (0.624)   Interpret the coefficients from this regression. Make sure to clearly indicate what is changing and what is constant in each interpretation.   Determine whether each coefficient is statistically significant at each of the conventional significance levels.   The R2 for this regression is 0.316. Interpret the meaning of this value.

Suppose the following estimated regression equation was determined to predict salary based on years of experience. Estimated Salary = 29,136.63 +2257.51(Years of Experience) What is the estimated salary for an employee with 24 years of experience? Answer Keypad Keyboard Shortcuts Tables