A plot of residuals (vertical deviations from the regression line) shows the errors or lack of fit, so it would indicate a good fit if the residuals are small, vs. over fit if they are large. Due to age related growth short pre teen, and a plateau after age 21, I would expect a linear regression would offer estimate age 5.5 years.
Answer:
$15 and 3600ft^2
Step-by-step explanation:
C) There are 16 white tiles used. The unit cost of a white tile=240/16=$15
E) The cafeteria area consists of 36 tiles of dimensions 10 ft x 10 ft, so the area of the floor is 3600ft^2
Answer:
C
B = 50°, a = 8.31, c = 11.7
Step-by-step explanation:
Answer:
216 ft³
Step-by-step explanation:
h*w*l=v
Part A
Correlation coefficient: -.99
This tells us that as time goes on (value of x increases) the area of the puddle goes down (value of y decreases)
Part B
y₂ - y₁
------- = slope
x₂ - x₁
9 - 15
--------
5 - 8
-6/-3 = 2
So the slope equals -2, regardless of the fact that we got 2 as an answer there, we know that it is a negative slope
Part C
The data represents causation because an increase in the value of x results in a decrease in the value of y, this shows an example of direct causation between x and y.
