The school’s guidance department compares the grade-point averages and standardized state test scores for 10 students in each grade. the table below shows the correlation coefficient for each data set.

grade level and correlation coefficient

9th grade 0.3
10th grade –0.1
11th grade 0.2
12th grade –0.8

for which data set(s) is a linear regression model reasonable?

~ 9th grade and 11th grade data sets
~ 10th grade data set
~ 10th grade and 12th grade data sets
~ 12th grade data set

3.4 pizzas

step-by-step explanation:

given is a scatter plot showing number of pizzas sold during weeks for different issues of coupon

y represents number of pizzas sold and x number of coupons issued

y is marked verticaly and x horizontally

the trend line is given as

y =3.4x+43

this says that even when no coupon is issued pizzas sold will be 43

and rate of change of pizza sold for 1 unit of coupon = slope = 3.4

i.e. when x increases by 1 unit y increases by 3.4 units

hence for each additional coupon issued 3.4 pizzas more will be sold

to plot points   for x just start at the origin (middle) and go to the left however many times it say(if the number is a positive) if the number is a negative then go right however many times it says if it is 0 go nowhere

now keep you pencil there and go up however many times it says on y(if it is positive) if it is negative then go down however many times it says. if it says 0 go nowhere.

you have just plotted a point! now when you finish plotting all of them connect them with a ruler

plot each point as (-3, 7), (0,4), (3,1), (8,-4)   in the parenthesis on the left of the comma is x and the right is y.