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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The total cost for a 6-month plan for n lines is represented by the equation:
Cost = 660n + 100
This equation is in the slope intercept form. The coefficient of n represents the slope here.
In the given scenario the slope can be interpreted as the total variable cost for one line for a period of 6 months.
The variable costs are associated with a line are:
1) Unlimited data cost ($40 per month). So for 6 months this cost will be $240
2) Unlimited Call cost ($10 per month). So for 6 months this cost will be $60
3) Unlimited Text Message Cost ($10 per month). For 6 months this cost will be $60.
4) Cost of Phone ($300 per line)
Adding these costs up we get: 240 + 60 + 60 + 300 = $660
Thus, 660 represents the total cost per line for unlimited data, calls, text message and one phone for 6 months. Therefore, option A gives the correct answer.
Answer:
24
Step-by-step explanation:
54/36=1.5
1.5*16=24