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:
Measure of the arc = 360-74° = 286°
An arc measure is the measure of an angle that the arc creates in the center of a circle.
Answer:
0 ≥ -7
Step-by-step explanation:
3(n + 5) ≥ 3n + 8
3n + 15 ≥ 3n + 8
3n - 3n ≥ 8 - 15
0 ≥ -7
Answer:
A
Hope this helps
Step-by-step explanation:
Answer:
1.) 18 is decreasing by 83%
2.) 16 is decreasing by 12.5%
Step-by-step explanation:
Part ÷ Whole = Percent (decimal form)
1.) First, you subtract the smaller number from the larger number: 18 - 3 = 15. Then you find the percent of the part: 15 ÷ 18 = 0.833333333333. This can be rounded to 0.83. Multiply 0.83 by 100 to get the percentage: 0.83 • 100 = 83%. To check your answer, multiply 0.83 by 18. It checks out. 18 is being <em>decreased</em> by 83%.
2.) Subtract 14 from 16 to get 2. Then divide 2 by 16: 2 ÷ 16 = 0.125. Multiply that by 100: 0.125 • 100 = 12.5%. To check this, we multiply 0.125 • 16 = 2. It works. So, 16 is being <em>decreased</em> by 2%.
Hope this helps,
♥<em>A.W.E.</em><u><em>S.W.A.N.</em></u>♥
