A professor has found that scores on the midterm exam in her classes predict scores on the final exam. The regression constant in the linear prediction rule for predicting final exam scores from midterm exam scores is 36 and the regression coefficient is 0.5. Complete parts (a) through (k) below. (a) Indicate the predictor variable. The predictor variable is the midterm exam score. (b) Indicate the criterion variable. The criterion variable is

We expect a car's highway gas mileage to be related to its city gas mileage (in miles per gallon, mpg). Data for all 1259 vehicles in the government's 2019 Fuel Economy Guide give the regression line highway mpg = 8.720 + (0.914x city mpg) for predicting highway mileage from city mileage. 1 O Macmillan Learning (b) What is the intercept? Give your answer to three decimal places. intercept: Why is the value of the intercept not statistically meaningful? The value of the intercept is an average value calculated from a sample. The value of the intercept represents the predicted highway mileage for city gas mileage of 0 mpg, and such a prediction would be invalid since 0 is outside the range of the data. The value of the intercept represents the predicted highway mileage for slope 0. O The value of the intercept represents the predicted city mileage for highway gas mileage of 0 mpg, and such a car does not exist. mpg

Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS df 208.008457 314.295372 37 2 104.004228 8.49446952 MS 522.303829 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared Root MSE = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What is the predicted height for a child born to a mother…

The data show the chest size and weight of several bears. Find the regression​ equation, letting chest size be the independent​ (x) variable. Then find the best predicted weight of a bear with a chest size of 43 inches. Is the result close to the actual weight of 237 pounds? Use a significance level of 0.05. Chest_size_(inches) Weight_ (pounds)50                              27954                              33944                              21954                              29240                                20136                                116 Is the result close to the actual weight of 237 ​pounds? A. This result is close to the actual weight of the bear. B. This result is very close to the actual weight of the bear. C. This result is not very close to the actual weight of the bear. D. This result is exactly the same as the actual weight of the bear.