Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from a data set, the resulting regression equation is Weight=-2/4+0.426 Length + 12.1 Chest Size. The P-value is 0.000 and the adjusted R² value is 0.925. If an additional predictor variable of neck size (in.) is included, the P-value becomes 0.000 and the adjusted R² becomes 0.933. Why is it better to use values of adjusted R² instead of simply using values of R²? Choose the correct answer below. C O A. The unadjusted R² can only be calculated for regression equations with P-values greater than 0, while the adjusted R² can be calculated for regression equations with any manner of P-value. OB. The unadjusted R² increases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. OC. The unadjusted R² decreases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. O D. The unadjusted R² can only be calculated for regression equations with two or fewer predictor variables, while the adjusted R² can be calculated for regression equations with any number of predictor variables.

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 39 inches. Is the result close to the actual weight of 236 pounds? Use a significance level of 0.05. Chest size (inches) 44 41 41 55 51 42 Weight (pounds) 213 206 176 309 300 178 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y = x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 39 inches? The best predicted weight for a bear with a chest size of 39 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 236 pounds? A. This result is close to the actual weight of the bear. B. This result is exactly the same as the actual weight of the bear. O C. This result is not very close to the actual weight of the bear. O…

intents d Resource Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.1 mm. How does the result compare to the actual height of 1776 mm? Foot Length 282.4 277.9 253.4 259.3 279.2 258.2 273.6 262:3 Height 1785.1 1770.9 1676.0 1646.1 1859.0 1710.1 1789.3 1736.9 The regression equation is y=+x. (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) ype here to search Tutoring Help me solve this O i Get more help. C 3¹ ... 99+ 0 LA 6 3 Clear all Check answer 78°F ^®

The relationship between the number of games won by a minor league baseball team and the average attendance at their home games  is analyzed. A regression to predict the average attendance from the number of games won has an R2 = 25.6%. The residuals plot indicated that a linear model is appropriate. What is the correlation between the average attendance and the number of games won. A. 0.066 B. 0.863 C. 0.506 D. 0.744 E. 0.256