MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Given
The typical deviation about (English score = 17.84 + 0.729*Math score) is 14.3, and the typical
deviation about (Math score = 3.45+0.933*English score) is 16.22.
Considering both se and r2
, which equation is more useful to predict the marks? Why.
Transcribed Image Text:The data below show the scores of the math exam and English exam of 20 students.
Math Exam
English Exam
70
74
45
50
26
30
84
70
23
30
88
80
75
85
99
100
100
100
100
40
20
30
46
65
42
45
74
80
56
60
12
20
65
65
80
80
66
75
87
95
The Math teacher thought of using the English exam marks as well to predict the math
exam marks.
The least squares regression line to predict the math exam scores was calculated:
Math score = 3.45+0.933*English score
1. Find the coefficient of determination of the new data where x-English score and y=Math
score.
Interpret the value in the context.
2. For the same unusual point found in part 1, what do you expect the sign of the residual of that
point would be? Why?
3. Calculate the residual for that point.
4. A student got 45 in his English exam. Knowing that the residual is equal to 4.565, what is his
exact math exam score?
Given
The typical deviation about (English score = 17.84 + 0.729*Math score) is 14.3, and the typical
deviation about (Math score = 3.45+0.933*English score) is 16.22.
Considering both se and r2, which equation is more useful to predict the marks? Why.
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