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:
x=4
Step-by-step explanation:
Remove the parentheses and turn the 4-2x and make it into 4+2x candle the equal term -4 and should be left with x+6=2+2x then move the variable to the left and change the sign so it would be x-2x=2-6 and collect like terms so it would be -x=2-6 and then calculate that and get -x= -4
(sorry its alot)
the three numbers are 49,56 and 63.
Answer: 390 miles
Step-by-step explanation:
Answer:
5.
Step-by-step explanation:
x axis is the same. do 7-2. Which equls 5.