Question

a) A regression line is useful for predicting
Answer values.
b) The
Answer
variable is the x-value, and the
Answer
is the y-value.
c) The
Answer
of a regression line tells you the rate of change. If it is positive, there is a
Answer correlation.
If it is negative, there is a
Answer correlation.
d) The constant term in the regression line frequently predicts a
Answer value.
Example: The regression line modeling the number of push-ups Juan does each day is y = 0.631x + 0.0357.
e) The explanatory variable is
Answer
f) The response variable is Answer, •
g) Juan increases the number of push-ups he does by about
1 Answer
each day.
h) There is a
Answer
correlation between time (in days) and the number of push-ups Juan does.
:: time (days)
:: starting
the number of push ups
# explanatory
positive
#unknown
::slope
positive
:: 0.631
# negative
::response

Answer 1

Here are the answers filled in as per your request:

a) A regression line is useful for predicting **response** values.

b) The **explanatory** variable is the x-value, and the **response** is the y-value.

c) The **slope** of a regression line tells you the rate of change. If it is positive, there is a **positive** correlation. If it is negative, there is a **negative** correlation.

d) The constant term in the regression line frequently predicts a **starting** value. Example: The regression line modeling the number of push-ups Juan does each day is y = 0.631x + 0.0357.

e) The explanatory variable is **time (days)**.

f) The response variable is **the number of push-ups**.

g) Juan increases the number of push-ups he does by about **0.631** each day.

h) There is a **positive** correlation between time (in days) and the number of push-ups Juan does.