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:
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Answer:
Step-by-step explanation:
 
        
             
        
        
        
Answer:
C. one solution 
Step-by-step explanation:
The number of solutions can be found from the number of intersection points. 
There are 2 lines, a parabola (curve) and a horizontal line that is parallel to the x axis. 
We see that there is 1 point of intersection between the 2 lines, at (2,1)-right 2 and up 1. Therefore, this non linear system has 1 solution. 
C. one solution is the correct answer. 
 
        
             
        
        
        
Answer: -28
Step-by-step explanation: