Answer:
The standard deviation of the residuals calculates how much the data points spread around the regression line. The result is used to measure the error of the regression line's predictability.
Step-by-step explanation:
<h2>How do you find the standard deviation around the regression line?</h2>
STDEV. S(errors) = (SQRT(1 minus R-squared)) x STDEV. S(Y). So, if you know the standard deviation of Y, and you know the correlation between Y and X, you can figure out what the standard deviation of the errors would be be if you regressed Y on X.
<h2>What does standard deviation tell you?</h2>
A standard deviation (or σ) is a measure of how dispersed the data is in relation to the mean. Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.
Answer:
yes to both
Step-by-step explanation:
(1) For y=1, and x=a, ...
a² + 1² ≤ 3
-√2 ≤ a ≤ √2 . . . . . subtract 1 and take the square root
All values of "a" are less than 2 inside the circle.
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(2) For y=4 and x=a, ...
2·4 +4·a = 10
4a = 2 . . . . . . . subtract 8
a = 1/2 . . . . . . .divide by 4
The value of "a" for point (a, 4) on the line is less than 2.
Answer:
Step-by-step explanation:
$5=movie tickets
$3=snacks
they need a total of: $300
standard form is: Ax+By=C
the equation in standard form would be: 5x+3y=300
Answer:
what do you mean by models? equations or experiments?
Step-by-step explanation:
Addition or something else i think 11x 5
