Answer:
G) Yes, because the plots and the linear model both align to produce a similar calculated sum.
H) I need to see the data table again for step 2d.
Step-by-step explanation:
1.) You scatter plot should be off by 6.97, since that was the first difference in your data table set of terms.
Basically subtract all of the GPAs from the Hours in the table.
Ex). Hours - GPA = Difference
or like before,
9.2 - 2.23 = 6.97
Do the rest of the numbers like this then plot the answers. I'd advise you plot your second set of scatter plot points in a different color.
Answer:
4
out of
32
−
4
x
.
4
(
8
−
x
)
Step-by-step explanation:
Let
A = event that the student is on the honor roll
B = event that the student has a part-time job
C = event that the student is on the honor roll and has a part-time job
We are given
P(A) = 0.40
P(B) = 0.60
P(C) = 0.22
note: P(C) = P(A and B)
We want to find out P(A|B) which is "the probability of getting event A given that we know event B is true". This is a conditional probability
P(A|B) = [P(A and B)]/P(B)
P(A|B) = P(C)/P(B)
P(A|B) = 0.22/0.6
P(A|B) = 0.3667 which is approximate
Convert this to a percentage to get roughly 36.67% and this rounds to 37%
Final Answer: 37%
Let T = number of tickets and P = number of popcorn containers. Then
