The residuals are the difference between the dataset values and the values computed from the regression formula. Here is a plot.
Answer:
I THINK the answer is ⊥, I'm really not confident on this one.
https://mathbitsnotebook.com/Geometry/CongruentTriangles/CTtriangleMethods.html <-- this can help you
Answer:
The answer would be 10/16.
Hope this helps!
Brianliest?
Answer:
a) 
b) 
c) "a.The mean of the sampling distribution stays the same, but the standard error decreases."
Step-by-step explanation:
a) We have a population with mean of 14.7 and standard deviation of 3.2.
We have to calculate the parameters of the sampling distribution (mean and standard deviation), for a sample size of n=100.
The mean for the sampling distribution is the same of the population:

The standard deviation of the sampling distribution is related to the population standard deviation by the inverse of the square of the sample size:

b) For a sample size of n=400, the mean is the same (14.7), but the standard deviation becomes:

c) "a.The mean of the sampling distribution stays the same, but the standard error decreases."
As we calculated, the standard error decreases as the sample size increases. This is because the variability of the variable is reduced as the sample size is bigger.
The mean stays the same independently of the sample size.