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:
You might be interested in
<h3>Answer: Choice D</h3>
======================================================
Explanation:
The inequality sign has an "or equal to", which means the boundary line will be solid. We can rule out choices B and C because they have dashed boundary lines.
A solid boundary line means that points on the boundary are part of the solution set.
Now let's see what happens when we plug in a point like (x,y) = (4,0). This will tell us how to shade the blue region.
This is false because -20 is not larger than -1. It's the other way around.
This tells us the point (4,0) is not in the blue shaded region, and it's not on the boundary line either. We can rule out choice A because of this.
The only thing left is choice D, which is the final answer. I recommend plugging a point from this region into the inequality to confirm we have a true statement.