Again using the NHIS data set, we explore possible predictors of body mass index (BMI). We perform a linear regression, modeling BMI as the dependent variable, and using age (in years), education (in years), and the number of times per week someone engages in moderate to vigorous physical activity, as independent variables. Based on the results of this regression, answer the questions below. y I C091: Std EH" t P) I tl Standardized Coef. ______________ +________________________________________________________________ Age I 910 992 4.332 999 033 Education I - 146 611 4.2.492 036 - 995 ACtiVity/WEEKI - 023 011 -2.B77 038 - 015 _cons I 27 819 298 133.972 999 8) The interpretation of the coefcient for activity per week is a. For each additional time per week someone engages in moderate/vigorous activity, age and education decrease by .023, all other things held constant. b. For each additional point of BMI, someone engages in moderate/'vigorous activity increases by .023 times per week, all other things held constant. c. For each additional time per week someone engages in moderate/vigorous activity, BMI decreases by .023 points, all other things held constant. (1. For each additional time per week someone engages in moderate/vigorous activity, BMI decreases by 2.3 percent, all other things held constant