Answer:
Hence P values of beta becomes smaller(< 0.0001). and doest affect the mean response
Step-by-step explanation:
Given:
AS Predictor become more highly correlated .
To find:
Descriptive Nature of high correlated Predictor .
Solution:
A predictor is high correlated means:
1)It means that the two variables are strongly related to each other.
2)This is also called as problem of multicollinearity when two variables are
in Regression.
Effects when predictor are highly correlated ;
- <em>The estimated coefficient of one any one variable depends on the other predictor variable in model.</em>
- <em>Estimated coefficient of regression decrease as predictor variables are added.</em>
- <em>Hypothesis test Beta = zero gives different conclusion depending upon variable.</em>
- <em>High correlated of predictor variable does not provide good precision of predication of response in within model.</em>
In short ,Mulitcollinearity does not affect the mean response and new response of the model.
Hence P values of beta becomes smaller(< 0.0001). and doest affect the mean response
Answer:
weight on saturn = (weight on earth/9.8) x 10.44
So,
3.24 = (x/9.8) x 10.44
0.3103 = x/9.8
x = 3.0409
The rock would weigh 3.0409 pounds on Earth! :)
What are the next three terms in the sequence 2, -4, 8, -16, 32, ...? A. -128, 256, -512 B. 160, 320, 640 C. 160, -320, 640 D. -
miv72 [106K]
Common ratio is -2
next 3 terms :
32 * -2 = -64
-64 * -2 = 128
128 * -2 = -256
answer is D
I believe u can put 5 books on there