ŷ= 1.795x +2.195 is the equation for the line of best fit for the data
<h3>How to use regression to find the equation for the line of best fit?</h3>
Consider the table in the image attached:
∑x = 29, ∑y = 74, ∑x²= 125, ∑xy = 288, n = 10 (number data points)
The linear regression equation is of the form:
ŷ = ax + b
where a and b are the slope and y-intercept respectively
a = ( n∑xy -(∑x)(∑y) ) / ( n∑x² - (∑x)² )
a = (10×288 - 29×74) / ( 10×125-29² )
= 2880-2146 / 1250-841
= 734/409
= 1.795
x' = ∑x/n
x' = 29/10 = 2.9
y' = ∑y/n
y' = 74/10 = 7.4
b = y' - ax'
b = 7.4 - 1.795×2.9
= 7.4 - 5.2055
= 2.195
ŷ = ax + b
ŷ= 1.795x +2.195
Therefore, the equation for the line of best fit for the data is ŷ= 1.795x +2.195
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Answer:
The value of x is 8 gallon.
Step-by-step explanation:
Given a table showing approximate conversion from gallons to liters.
Number of Gallons 2 4 x
Number of Liters 7.6 15.2 30.4
We are required to find value of x,
Given : 2 gallon is equal to 7.6 liters.
⇒ 1 liter is equal to
liters. ........(1)
given, x gallon equal to 30.4 liters.
⇒ 1 liter is equal to
liters. .........(2)
from (1) and (2),
⇒ 
Solving for x, we get,
⇒ 
⇒ 
Approximately x = 8
Thus, the value of x is 8 gallon.
Answer:
1.8
Step-by-step explanation:
Answer:
X = -3
Step-by-step explanation:
Multiply both sides by 3
3x 1/3(3) = -3(3)
3x/3 = -9/3
divide both sides by 3 to isolate x
x = -3