25 : 9 = 2.777...
18
----
=70
63
-----
70
63
-------
70
63
----------
7
Answer:
Omg
Step-by-step explanation:
what in the world are you learning tip just pick a random answer
Answer:
-2 -27 the answer is -24
1 and 12 4
4 and 57 the answer is 53
10 and 147 the answer is 157
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
The answer to this question is B