Answer:
A.
- horizontal axis: kilometers ran per week
- vertical axis: weight in kilograms
B. The slope of the line of best fit is -0.291. It means for each additional km run per week, weight is predicted to be 291 grams less.
C. It means someone who ran 4.5 km per week had a weight of 86.5 kg.
D. 82.512 kg. A weight of 82.5 kg is expected to be associated with someone who runs 18 km/week. The data comes with no explanation, so we don't know any more than that.
Explanation:
A. The axes are labeled with what they represent.
B. The low and negative value of correlation coefficient means the slope is generally negative. A value of slope has been computed for the line of best fit. It is the coefficient of x in the equation of that line: -0.291.
The axes of the graph tell you it means the predicted weight is about 291 grams less for each km run per week. The explanation that should accompany the graph will tell you what it means in terms of the experiment run or the population surveyed.
C. The first number of the ordered pair is interpreted using the meaning of the horizontal axis; the second number is interpreted according to the meaning of the vertical axis. We know what the labels are, but we have no description of their meaning.
D. Put 18 for x in the equation and do the arithmetic.
... y = 87.75 - 0.291×18 = 82.512 . . . . kg
The line of best fit is used to make predictions. It works by putting a value into the equation in place of the independent variable, then evaluating the equation to see what value is predicted for the dependent variable. In that way, it is no different from evaluating any other equation.
Here, the problem statement does not supply sufficient information for us to be able to tell what, exactly, we are predicting. The label on the graph says it is "weight in kilograms," but we have no idea what that weight refers to.