Each description on the left is written about the linear regression findings on the right. Fill in the blanks using the information in the line of best fit and the r-value.

1

For every additional Marvel Universe movie released each year, the average person is predicted to consume [amount] [more / fewer] pounds of sugar! This correlation is [strong, moderate, weak, practically non-existent].

 
 f(x) = −3.19x + 12
 r = −0.05

2

Shoe size and height are [strongly, moderately, weakly, not], [positively / negatively] correlated. If person A is one size bigger than person B, we predict that they will be roughly [amount] inches taller than person B as well.

 
f(x) = 1.65x + 52
r = 0.89

3

There is [a strong, a moderate, no] relationship found between the number of Uber drivers in a city and the number of babies born each year.

 
f(x) = 0.012x + 7.8
r = 0.01

4

The correlation between weeks-of-school-missed and SAT score is [strong, moderate, weak, practically non-existent] and [positive / negative]. For every week a student misses, we predict a [amount] point [gain / drop] in their SAT score.

 
f(x) = -15.3x + 1150
r = −0.65

5

There is a [strong, moderate, weak, practically non-existent], [positive / negative] correlation between the number of streaming video services someone has, and how much they weigh. For each service, we expect them to be roughly [amount] pounds heavier.

 
f(x) = 1.6x + 160
r = 0.12

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