Umm.. hundredth thousandth
I think the answer would be <span>3.38461
</span>
5. D (the number under the square root symbol must be greater than or equal to 0.
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
67.67 where the first one was the best in my opinion I was a bit confused when it came out of my mind that it is
Just expand each number after the decimal. 0.300+0.030+0.004