Please help answer this, I do not know how. The data from data321.dat contains i

Question

Please help answer this, I do not know how.

The data from data321.dat contains information on 78 seventh-grade students. We want to know how well each of IQ score and self-concept score predicts GPA using least-squares regression. We also want to know which of these explanatory variables predicts GPA better. Give numerical measures that answer these questions. (Round your answers to three decimal places.) (Regressor: IQ) R 2 Regressor: Self-Concept) R Which variable is the better predictor? Self Concept

Explanation / Answer

I will be using R programming to solve your problem.
I am providing you with the R code and I will also provide you with the output and explanations of the R codes.

data=read.csv("C:\Users\LAPTOP\Desktop\a.csv")
data
attach(data)
names(data)

Here, I loaded the data, that you provided, on to the R programming console by storing the data in a CSV (Comma Separated Value) file and then loaded it using the "read.csv" command. The "attach" command helps us to access the variables that are used in the dataset and the "names" command helps us to see the names of the variables.

lm1=lm(gpa ~ iq,data)

Here, I have fitted a linear regression model between GPA and IQ via least squares regression. This will give us the R squared value.

summary(lm1)

This command is used to find out the R-squared value, the regression coefficients of the model and their significance, etc. The R-squared values so obtained are as given below. We shall consider the Adjusted R-squared value, since it is better than Multiple R-squared value.

Multiple R-squared: 0.5004, Adjusted R-squared: 0.4939

lm2=lm(gpa ~ concept,data)

Here, I have fitted a linear regression model between GPA and Self-Concept via least squares regression. This will give us the R squared value.

summary(lm2)

This command is used to find out the R-squared value, the regression coefficients of the model and their significance, etc. The R-squared values so obtained are as given below. We shall again consider the Adjusted R-squared value, since it is better than Multiple R-squared value.

Multiple R-squared: 0.3, Adjusted R-squared: 0.2908

Now, if regressor is IQ, then R-squared value came out to be 0.493 and if the regressor is Self-Concept, then R-squared value came out to be 0.291.

Hence, we can say that IQ is a better regressor than Self-Concept, due to the R-squared value.

(Note: R-squared value is used to find out the goodness of fit of a regression model)

Related Questions

Navigate

• Browse (All)
• Browse P
• Subjects

---

---

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