4. Y = 0.43X + 1.1; X = 0.97 5. Y = X +:X = 6. Assume that the height of fathers (X) and the height of their eldest sons (Y) were significantly correlated. The equation of the regression line is Y = 0.23X + 134. Given the height of your own father, predict the height of his eldest son. The height is expressed in centimeters.
4. Y = 0.43X + 1.1; X = 0.97 5. Y = X +:X = 6. Assume that the height of fathers (X) and the height of their eldest sons (Y) were significantly correlated. The equation of the regression line is Y = 0.23X + 134. Given the height of your own father, predict the height of his eldest son. The height is expressed in centimeters.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Answer 4 to 6 only. Thank you.
Transcribed Image Text:EXAMPLES
Example 1
In the regression line Y = 6X + 9, predict the value
Eхample 2
A significant relationship exists between the test
scores in Mathematics (X) and the final grade in
Mathematics (Y) of grade 11 learners. The regression
line is given by the equation Y = 0.3X + 80.9. Predict
the final grade of a learner when her test score is 35.
of Y when the value of X is 7.
Solution:
Step 1. Copy the linear equation.
Y = 6X + 9
Step 2. Substitute the value of X in the equation
Since X = 7,
Solution:
Step 1. Copy the linear equation.
Y = 6(7) + 9
Y = 0.3X + 80.9
Step 2. Substitute the value of X in the equation
Since X = 35,
Step 3. Solve for Y
Y = 42 +9
Y = 51
Y = 0.3(35) + 80.9
Therefore, we can predict that Y is 51 when X is 7.
Step 3. Solve for Y
Y = 10.5 + 80.9
Y = 91.4
| Therefore, we can predict that the final grade of the
| learner is 91.4 (or 91) when she scores 35 in the
Mathematics test.
Transcribed Image Text:ACTIVITY
Predict the value of Y given the regression line and the value of X in each item.
1. Y = 0.4X + 11; X = 2.5
2. Y = 21X + 123; X = 29
3. Y = 70X + 59; X = 38
4. Y = 0.43X + 1.1; X = 0.97
5. Y = X +;X =
6. Assume that the height of fathers (X) and the height of their eldest sons (Y) were significantly correlated. The
equation of the regression line is Y = 0.23X + 134. Given the height of your own father, predict the height of
his eldest son. The height is expressed in centimeters.
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