Answer: VIICCCXLVII
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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:
Total amount of fencing needed as an algebraic expression in terms of x is: <em>10x</em><em> </em><em>+</em><em> </em><em>3</em> .
Step-by-step explanation:
As it is given that each rectangle has the same dimensions, the dimensions of each rectangle must be: x units by 2x + 1 units.
Based on this, we can calculate the total amount of fencing needed.
Let width of each rectangle = x
Let length of each rectangle = 2x + 1
There are 4 widths and 3 lengths in total of fencing.
Therefore:
= 4 ( x ) + 3 ( 2x + 1 )
Expand:
= 4x + 6x + 3
Group like-terms:
= 10x + 3