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:
m∠QTR = 98°
Step-by-step explanation:
From the picture attached,
Radii of the circle are TQ and TR measuring equal lengths.
Therefore, ΔTQR is a isosceles triangle.
Opposite angles of the equal sides will be equal in measure.
m∠RQT = m∠TRQ = 41°
By angle sum theorem,
m∠RQT + m∠TRQ + m∠QTR = 180°
41° + 41° + m∠QTR = 180°
m∠QTR = 180° - 82°
= 98°
Therefore, m∠QTR = 98°
Answer:
3 packs
Step-by-step explanation:
1 pack = $3
To see how many she could buy divide the money she has by how much each pack costs
9/3 = 3
$3 for each pack is the same as
3+3+3 = 6+3 = 9