In a teacher's math course, a linear regression line was calculated to predict
1 answer:
The given equation is the best line that approximates the linear
relationship between the midterm score and the score in the final exam.
- AJ's residual is 0.3, which is not among the given options, therefore, the correct option is. <u>E. None of these</u>.
Reasons:
The given linear regression line equation is; = 25.5 + 0.82·
Where;
= Final exam score;
= The midterm score;
AJ score in the first test, = 90
AJ's actual score in the exam = 99
Required:
The value of AJ's residual
Solution:
By using the regression line equation, we have;
The predicted exam score, = 25.5 + 0.82 × 90 = 99.3
- The residual score = Predicted score - Actual score
∴ AJ's residual = 99.3 - 99 = 0.3
AJ's residual = 0.3
Therefore, the correct option is option E;
- <u>E. None of these</u>
Learn more about regression line equation here:
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Hello!
I have attached three graphs. The first one for x = 7, second one for y = -1, and third one with both x = 7 and y = -1 on the same graph.
Hope this helps :))
I have attached three graphs. The first one for x = 7, second one for y = -1, and third one with both x = 7 and y = -1 on the same graph.
Hope this helps :))