Answer:
C
Step-by-step explanation:
A regression model is a function which can be used to predict behavior of the model. It takes data points in and forms a general pattern for the pattern using an equation. This model y = 12.3 + 0.12x is a linear regression model which means it has linear behavior (a line) where x is total yards gained and y is number of points scored. If one additional yard is gained then the score is likely to be 12.3 + 0.12(1) = 12.42. If two additional yards is gained then the score is likely to be 12.3 + 0.12(2) = 12.54. Notice the score increases by 0.12 points for every yard gained. This is answer choice C.
a.)The average points scored for teams who gain zero yards during a game is -12.3 points.
b.) The average yards gained will increase by .12 for every additional point scored.
c.) The average change in points scored for each increase of one yard will be 0.12.
d.) The average number of points scored per game is 12.3.
Answer: -8 and -4
This is something you do through trial and error. Making a list or a table like shown below might help.
Answer:
Simon: 55 hours
Alvin: 70 hours
Theodore: <u>159</u> hours
Total: 284 hours
Step-by-step explanation:
Let A, T, and S stand for the hours worked by Alvin, Simon, and Theodore.
We are told that:
A = S + 15,
T = 3S - 6
and
A + S + T = 284
Note that the first two equations state the value of A and T in terms of S. Let's use them in the third equation, so that we'll have only one unknow:
A + S + T = 284
(S + 15) + S + (3S - 6) = 284
5S + 9 = 284
<em><u>S = 55</u></em>
Now use this value of S in the first two equations to find A and T:
A = S + 15
A = 55 + 15
<u><em>A = 70</em></u>
T = 3S - 6
T = 3*55 - 6
<em><u>T = 159</u></em>
<u></u>
<u>(55 + 70 + 159) = 284</u>
<u></u>
No because of how the slope is
