Which characteristic of a data set makes a linear regression model unreasonable?
Answer: A correlation coefficient close to zero makes a linear regression model unreasonable.
If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable. For a linear regression model to be reasonable, the most important check is to see whether the two variables are correlated. If there is correlation between the two variable, we can think of regression analysis and if there is no correlation between the two variable, it does not make sense to apply regression analysis.
Therefore, if the correlation coefficient is close to zero, the linear regression model would be unreasonable.
Answer:
Step-by-step explanation:
A= 1/2 bh
10.98 = 1/2b (3.6)
10.98=b/2 (3.6)
10.98=b (1.8)
10.98/1.8=b
6.1=b
Step-by-step explanation:
∆PQR similar to ∆ JKL
JK/KL= PQ/QR
6/12=3/QR
QR=3×2= 6
therefore, tan(R) = PQ/QR = 3/6=1/2
and, tan(J) = KL/JK =12/6=2
tan(J)=4.tan(R)
option D
The answer is the third one aka C.
There must not be two points on the same y-axis because that doesn't make a function but a relation instead.
C. doesn't have 2 points on same y-axis and therefore the third picture is the relation that's a function.
Multiply 64 times .30 =?
Then take the answer you get and subtract it from $64 then you should get your answer of $44.80 please work it out it’s not too hard it is actually pretty easy.
Hope this helps
