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:
k=0
Step-by-step explanation:
3k+6-3=3
3k = 3+3-6
3k = 6-6
3k = 0
k = 0
Answer: I think it's 662.4
Please correct me if I'm wrong.
Answer:
OPTION B - 41
Step-by-step explanation:
An expression is given and the corresponding values for the expression are also given. We have to substitute the given values to arrive at the answer.
The given expression is: x + 3y + z.
Also given: x = 4, y = 5, z = 22.
Substitute these values in the above expression, we get:
4 + 3(5) + 22 = 4 + 15 + 22 = 41.
∴ x + 3y + z = 41
