Welcome to the Scoping Rules and Debugging MCQs Page
Dive deep into the fascinating world of Scoping Rules and Debugging with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Scoping Rules and Debugging, a crucial aspect of R Programming. In this section, you will encounter a diverse range of MCQs that cover various aspects of Scoping Rules and Debugging, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within R Programming.
Check out the MCQs below to embark on an enriching journey through Scoping Rules and Debugging. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of R Programming.
Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Scoping Rules and Debugging. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!
Scoping Rules and Debugging MCQs | Page 2 of 6
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function(p) {
params[!fixed] <- p
mu <- params[1]
sigma <- params[2]
## Calculate the Normal density
a <- -0.5*length(data)*log(2*pi*sigma^2)
b <- -0.5*sum((data-mu)^2) / (sigma^2)
-(a + b)
}
> ls(environment(nLL))> nLL <- make.NegLogLik(normals, c(FALSE, 2))
> optimize(nLL, c(-1, 3))$minimum> nLL <- make.NegLogLik(normals, c(1, FALSE))
> optimize(nLL, c(1e-6, 10))$minimum> g <- function(x) {
+ a <- 3
+ x+a+y
+ ## 'y' is a free variable
+ }
> y <- 3
> g(2)Suggested Topics
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