Explore topic-wise MCQs in R Programming.

This section includes 4 Mcqs, each offering curated multiple-choice questions to sharpen your R Programming knowledge and support exam preparation. Choose a topic below to get started.

1.

In the mathematical Equation of Linear Regression Y = β1 + β2X + ϵ, (β1, β2) refers to __________

A. (X-intercept, Slope)
B. (Slope, X-Intercept)
C. (Y-Intercept, Slope)
D. (slope, Y-Intercept)
E. (Slope, X-Intercept)c) (Y-Intercept, Slope)d) (slope, Y-Intercept)
Answer» D. (slope, Y-Intercept)
2.

Function used for linear regression in R is __________a) lm(formula, data)b) lr(formula, data)c) lrm(formula, data)d) regression.linear(formula, dat

A. lm(formula, data)
B. lr(formula, data)
C. lrm(formula, data)
D. regression.linear(formula, data)
Answer» B. lr(formula, data)
3.

Which of the following metrics can be used for evaluating regression models?

A. ii and iv
B. i and ii
C. ii, iii and iv
D. i, ii, iii and ivView Answer
Answer» E.
4.

In practice, Line of best fit or regression line is found when _____________a) Sum of residuals (∑(Y – h(X))) is minimumb) Sum of the absolute value of residuals (∑|Y-h(X)

A. Sum of residuals (∑(Y – h(X))) is minimum
B. Sum of the absolute value of residuals (∑|Y-h(X)|) is maximum
C. Sum of the square of residuals ( ∑ (Y-h(X))2) is minimum
D. Sum of the square of residuals ( ∑ (Y-h(X))2) is maximum
Answer» D. Sum of the square of residuals ( ∑ (Y-h(X))2) is maximum