Answer:
Depending upon the golf score predictors we can conclude the answer from given Conditional statements
If Someone want Total golf score better then, following .condition
Yes, Because R squared is close to 1 . ....(If Regression values are prefect to fit with model then only)
<em>(But the data is not sufficient to say 100%, it depends on score given)</em>
Step-by-step explanation:
Given :
Explanatory Question on r-squared in regression.
To Find :
Does regression equation help us to know total golf score much better.
Solution;
As in Question there is no golf score given so we cant see "yes" or "no".
But we can be conditional here ,
1) If golf score to be accurate then , multiple regression predict points should fit the model prefect ,hence the R squared value "<em>must be close to 1</em>" .
2) If gold score is not accurate then multiple regression suggest that model does not explain any variables, no linear relationship.
then r squared value <em>"must not be close to 1".</em>
Depending upon the golf score predictors we can conclude the answer from given Conditional statements.
that Yes, Because R squared is close to 1 .
126/60=21/10 and 21/10 as a mixed number is 2 1/10 so your answer is 2 1/10. Hoped I helped. :)