We square the residuals when using the least-squares line method to find the line of best fit because we believe that huge negative residuals (i.e., points well below the line) are just as harmful as large positive residuals (i.e., points that are high above the line).
<h3>What do you mean by Residuals?</h3>
We treat both positive and negative disparities equally by squaring the residual values. We cannot discover a single straight line that concurrently minimizes all residuals. The average (squared) residual value is instead minimized.
We might also take the absolute values of the residuals rather than squaring them. Positive disparities are viewed as just as harmful as negative ones under both strategies.
To know more about the Least-Squares Line method, visit:
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(13/4)*3 = 39/4 ft
I believe that's the answer
both (0,350) and (250,700) fall in the shaded are
and check:
350 *3 = 1050, which is more than 1000 and more than double the amount of hotdogs ( 0)
700 *3 = 2100, so over 1000 and more than double the amount of hotdogs(250*2=500)
so those 2 are correct
Probability is about estimating or calculating how likely or 'probable' something is to happen.
The answer would be B. You multiply the 2 on both sides, getting 12 on the right. Then you divide by -1, and that switches the sign and makes 12 negative.