Intrigued by a 2013 study at the University of Nebraska that suggested marijuana smokers may be thinner than other adults, a group of students did a project to explore the relationship between body mass index (BMI) and amount of time spent under the influence of marijuana (measured in hours per week). Based on a random sample of 33 students at their university, they used BMI as the response variable. The equation of the least-squares regression line is: hours per month under influence = 49.2−1.15 BMI. Also, r2=0.134 .

this question is incomplete, the complete question is:

1. is this model effective

2. what is the correlation coefficient for this data.

3. for a student with a bmi of 25, what is the predicted number of hours under the influence.

Step-by-step explanation:

1. first of all this model is not effective because we have r² as 0.134. this tells us that only 13.4 percent of the of the variations that exist in this data has been explained by the model

1. we get the correlation coefficient by

the regression slope coefficient has a negative sign. this is what we would use in calculating the correlation coefficient.

= -√0.134

= -0.366

therefore the correlation coefficient is -0.366

2. to get the number of hours under the influence with a bmi of 25

the equation is

49.2-1.15bmi

= 49.2-1.15(25)

= 49.2-28.75

= 20.45

i don't see any

step-by-step explanation: