Answer:
y=1.003009+0.003453x
or
GPA=1.003009+0.003453(SAT Score)
Step-by-step explanation:
The least square regression equation can be written as
y=a+bx
In the given scenario y is the GPA and x is SAT score because GPA depends on SAT score.
SAT score (X) GPA (Y) X² XY
421 2.93 177241 1233.53
375 2.87 140625 1076.25
585 3.03 342225 1772.55
693 3.42 480249 2370.06
608 3.66 369664 2225.28
392 2.91 153664 1140.72
418 2.12 174724 886.16
484 2.5 234256 1210
725 3.24 525625 2349
506 1.97 256036 996.82
613 2.73 375769 1673.49
706 3.88 498436 2739.28
366 1.58 133956 578.28
sumx=6892
sumy=36.84
sumx²=3862470
sumxy=20251.42
n=13

b=9367.18/2712446
b=0.003453
a=ybar-b(xbar)
ybar=sum(y)/n
ybar=2.833846
xbar=sum(x)/n
xbar=530.1538
a=2.833846-0.003453*(530.1538)
a=1.003009
Thus, required regression equation is
y=1.003009+0.003453x.
The least-squares regression equation that shows the best relationship between GPA and the SAT score is
GPA=1.003009+0.003453(SAT Score)
Answer:
is the quotient
Step-by-step explanation:
We have two expression
and 
We need to find quotient of this expression using exponent law.
First we write as quotient form,




Thus,
is the quotient of
and
.
X=8
X=3
Sorry if it’s wrong
It would be 6 haha I just took a test and got it right
Answer:
C. quadratic function; quadratic term: −6x^2; linear term: −17x; constant term: −12
Step-by-step explanation:
Answer:
quadratic function; quadratic term: −6x² ; linear term: −17x; constant term: −12
Step-by-step explanation:
The given function is
We need to expand the RHS to get:
We can see that the degree of this polynomial function is 2 and hence it is a quadratic function.
The quadratic term is -6x²
The linear term is -17x
The constant term is -12