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:
1/8 of an hour
Step-by-step explanation:
3/4 x 1/6 = 3/24 = 1/8
Hope this helps!
Answer:
It would really depend on what the choices were.
Step-by-step explanation:
There are 2 roots for this equation.
The discriminant is given by b²-4ac. This is what goes under the square root in the quadratic formula. Since we will be taking the square root of this, if the discriminant is less than 0, there are no real roots; you cannot have a real square root of a negative number.
If the discriminant is equal to 0, there is 1 real root; the square root of 0 is 0, so the quadratic formula would yield one answer.
If the discriminant is greater than 0, there are 2 real roots. This is because taking the square root of a positive number gives a positive and negative result.
b in our equation is -7, a is 3 and c is 4:
b²-4ac = (-7)²-4(3)(4) = 49 - 48 = 1
There is 1 real root.
