There are three variables in the excel file: male coded or scored 1 if the stude

Question

There are three variables in the excel file:
male coded or scored 1 if the student was male, and coded or scored 0 if the student was female
gpa can range from 1.00 (very low grade point average) to 4.0 (very high grade point average)
image this variable captures a student’s perceived image of their weight and is scored: 1 = very underweight; 2 = underweight; 3 = about right; 4 = overweight; 5 = very overweight
On the image variable, then, students who report 4 or 5 perceive themselves as overweight. This variable, which basically serves as the dependent variable (Y) in the questions below, is an ordinal (rank order) variable. However, I would like for you to treat or consider this variable as an interval/ratio variable, which is very common in data analysis (i.e., treating ordinal variables as interval/ratio).
Once again, male is a nominal variable distinguishing males (=1) and females (=0), and GPA is an interval/ratio variable that can range from 1.00 to 4.00.

5a. Specifically, what would be the predicted score (Y-hat) on the weight image variable if a student had a GPA of 2.00?
5b. Generate the coefficient of determination for GPA (X) and image (Y) and interpret it.

male gpa image 0 1.50 3 0 3.25 3 0 3.00 3 0 3.00 3 0 4.00 3 0 2.50 3 0 3.25 4 0 2.75 4 0 3.75 3 0 3.00 3 0 4.00 3 0 3.50 3 0 4.00 3 0 2.75 2 0 1.75 5 0 2.25 3 0 3.33 3 0 3.75 3 0 4.00 2 0 3.25 3 1 2.75 3 1 2.75 3 1 2.75 3 1 2.25 4 1 3.00 2 1 3.25 3 1 2.25 4 1 1.75 2 1 2.25 3 1 3.25 3 1 1.00 4 1 3.00 2 1 2.50 3 1 2.00 4 1 2.25 3 1 2.75 3 1 3.00 2 1 3.50 3 1 3.75 2 1 2.50 3

Explanation / Answer

5a. Specifically, what would be the predicted score (Y-hat) on the weight image variable if a student had a GPA of 2.00?

------>

>D=read.table(file.choose(),header=TRUE,sep=',')
>attach(D)

> model=lm(image~gpa)
> model

Call:
lm(formula = image ~ gpa)

Coefficients:
(Intercept) gpa  
4.0343 -0.3508  

regression equation is

Image=4.0343 - 0.3508 *gpa

=4.0343 -0.3508 *2.00

= 3.3327

predicted score (Y-hat) on the weight image is 3.3327

5b. Generate the coefficient of determination for GPA (X) and image (Y) and interpret it.

> summary(model)$r.squared
[1] 0.1472856

So the coefficient of determination is 0.1472

Related Questions

Navigate

• Browse (All)
• Browse T
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.