Answer:
rom the relation for linear regression formula, Y = b·X + a, we have ;
For car 1
ΣXY = 102780
(ΣX)² = 36
ΣX = 6
ΣY = 52390
ΣX² = 14
N = 3
b = -1000
a = 19463
Y = -1000×X + 19463
For Car 2
ΣXY = 102539.8
(ΣX)² = 36
ΣX = 6
ΣY = 52346.6
ΣX² = 14
N = 3 .
b = -1076.7
a = 19602
Y = -1076.7×X + 19602
Step-by-step explanation:
part B ^
Since EF=FG, you can set 6x - 10 = to 3x + 11
Then add like terms
so,
Now you can divide by 3 to get
:)
then put it back into
so,
<span>In math notation, we've done this: z = (X - μ) / σ = (940 - 850) / 100 = 0.90
where z is the z-score
X is Vivian's score (940)
µ is the mean (850)
σ is the standard deviation (100)
As you may know, in a normal distribution it's expected that about 68% of all observations will fall within 1 standard deviation of the mean, 95% will fall within 2 standard deviations, and 99% will fall within 3 standard deviations.
940 lie before the first standard deviation, in which 16.5% is above it
since 940 is 0.9 from the mean and 0.1 from the first standard deviation
so above it is 17.5 % = 0.175 or about 0.18 </span>
Slope is 5
Y intersect is 0
Y= 5x
