Answer:
B. the variability around the regression line.
Step-by-step explanation:
The standard errors represents the distance (how sparse) the observed values fall from the regression line.
Standard errors for regression are measures of the spread of variables around the average (regression line)
The standard error is dependent on the standard deviation of the observations and the reliability of the test.
When the test is perfectly reliable, the standard error is zero and when unreliable, it is equal to the standard deviation of the observations.
What? are you trolling or is this a real problem lol
Answer:
The greatest common factor is 4 :)
Answer: A
Step-by-step explanation:
Because if she rode 10 mph means that she would ride 2.5 miles in 0.25 hours because if you divide 10 by 2.5 then you would get 0.25.
Answer:
Sclaene triangle
Step-by-step explanation:
