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
Learn more about regression equation on:
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Answer:
320 meters per minute, or 19,200 meters per hour
Step-by-step explanation:
please comment what the answer options are or what unit you need for the answer, i will change my answer accordingly. hope this helps :)
2r+7+2n+n2
Because I combined the ones with like terms.
The integral of e raised to x squared dx to the limit from 1 to 3 translating in equation we get
∫1-3 e^(X^2) dx.
Solving using scientific calculator, we have 1443.082471 or simply 1443.
<em>ANSWER: 1443</em>
Three would be your answer :)