Based on the computer output, the predicted price for a car with 10,000 miles is $22,347.20.
<h3>What is a least-squares regression?</h3>
A least-squares regression line can be defined as a standard technique in regression analysis and statistics that is typically used to make the vertical distance obtained from the data points running to the regression line to become very minimal or as small as possible.
In statistics, the sum of the residuals for a least-squares regression line is always zero (0) because it determines whether or not a line of regression is a good fit or match for the given data.
Based on the computer output, the predicted price for a car that has covered a distance of 10,000 miles on the odometer is $22,347.20.
Read more on least-squares regression here: brainly.com/question/26059078
Answer:
Explanation:
A line has a general equation of
where b is the y-intercept and slope of m.
Since 
is the value of y when 
, it is the point of intersection of the line with the y-axis, hence the y-intercept is 
.
We are given the slope is 
So the equation of the line is
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Below is the solution:
(a) <span>x bar = 3.
</span><span>n = 1
</span><span>std = 0.2
</span><span>z value = 1.645
</span>
<span>3 plus/minus 1.645 (0.2/(sqrt1))
</span>
<span>Interval = [3.07, 3.73]</span>
