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Here, you will find R Programming Quiz Answers in Bold Color which are given below. These answers are updated recently and are 100% correct✅ answers of LinkedIn R Programming Skill Assessment.
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Q1. How does a matrix differ from a data frame?
- A matrix may contain numeric values only.
- A matrix must not be singular.
- A data frame may contain variables that have different modes.
- A data frame may contain variables of different lengths.
Q2. What value does this statement return?
Q3. What do you use to take an object such as a data frame out of the workspace?
Q4. Review the following code. What is the result of line 3?
xvect<-c(1,2,3)xvect <- “2”xvect
-  1 2 3
-  “1” 2 “3”
-  “1” “2” “3”
-  7 9
Q5. The variable height is a numeric vector in the code below. Which statement returns the value 35?
Q6. In the image below, the data frame is named rates. The statement sd(rates[, 2]) returns 39. As what does R regard Ellen’s product ratings?
- sample with replacement
- trimmed sample
- sample <– not sure
Q7. Which choice does R regard as an acceptable name for a variable?
Q8. What is the principal difference between an array and a matrix?
- A matrix has two dimensions, while an array can have three or more dimensions.
- An array is a subtype of the data frame, while a matrix is a separate type entirely.
- A matrix can have columns of different lengths, but an array’s columns must all be the same length.
- A matrix may contain numeric values only, while an array can mix different types of values.
Q9. Which is not a property of lists and vectors?
Q10. In the image below, the data frame on lines 1 through 4 is names StDf. State and Capital are both factors. Which statement returns the results shown on lines 6 and 7?
Q11. Which function displays the first five rows of the data frame named pizza?
- BOF(pizza, 5)
- first(pizza, 5)
- top(pizza, 5)
- head(pizza, 5)
Q12. You accidentally display a large data frame on the R console, losing all the statements you entered during the current session. What is the best way to get the prior 25 statements back?
- history(max.show = 25)
Q13. d.pizza is a data frame. It’s column named temperature contains only numbers. If u extract temperature using the  accessors, its class defaults to numeric. How can you access temperature so that it retains the class of data.frame?
> class( d.pizza[ , “temperature” ] )> “numeric”
- class( d.pizza( , “temperature” ) )
- class( d.pizza[ , “temperature” ] )
- class( d.pizza$temperature )
- class( d.pizza[ , “temperature”, drop=F ] )
Q14. What does c contain?
a <- c(3,3,6.5,8)b <- c(7,2,5.5,10)c <- a < b
-  NaN
-  -4
-  4 -1 -1 2
-  TRUE FALSE FALSE TRUE
Q15. Review the statements below. Does the use of the dim function change the class of y, and if so what is y’s new class?
> y <- 1:9> dim(y) <- c(3,3)
- No, y’s new class is “array”.
- Yes, y’s new class is “matrix”.
- No, y’s new class is “vector”.
- Yes, y’s new class is “integer”.
Q16. What is mydf$y in this code?
mydf <- data.frame(x=1:3, y=c(“a”,”b”,”c”), stringAsFactors=FALSE)
- character vector
Q17. How does a vector differ from a list?
- Vectors are used only for numeric data, while list are useful for both numeric and string data.
- Vectors and lists are the same thing and can be used interchangeably.
- A vector contains items of a single data type, while a list can contain items of different data types.
- Vectors are like arrays, while lists are like data frames.
Q18. What statement shows the objects on your workspace?
Q19. What function joins two or more column vectors to form a data frame?
Q20. Review line 1 below. What does the statement in line 2 return?
1 mylist <- list(1,2,”C”,4,5)2 unlist(mylist)
-  1 2 4 5
-  “1” “2” “C” “4” “5”
-  1 2 C 4 5
Q21. What is the value of y in this code?
x <- NAy <- x/1
Q22. Two variable in the mydata data frame are named Var1 and Var2. How do you tell a bivariate function, such as cor.test, which two variables you want to analyze?
- cor.test(Var1 ~ Var2)
- cor.test(Var1,Var2, mydata)
Q23. A data frame named d.pizza is part of the DescTools package. A statement is missing from the following R code and an error is therefore likely to occur. Which statement is missing?
library(DescTools)deliver <- aggregate(count,by=list(area,driver), FUN=mean)
- mean <- rbind(d.pizza,count)
Q24. How to name rows and columns in DataFrames and Matrices F in R?
- data frame: names() and rownames() matrix: colnames() and row.names()
- data frame: names() and row.names() matrix: dimnames() (not sure)
- data frame: colnames() and row.names() matrix: names() and rownames()
- data frame: colnames() and rownames() matrix: names() and row.names()
Q25. Which set of two statements-followed by the cbind() function-results in a data frame named vbound?
- [ ] v1<-list(1,2,3)
- [ ] v1<-c(1,2,3)
- [ ] v1<-c(1,2,3)
Q26. ournames is a character vector. What values does the statement below return to Cpeople?Cpeople <- ournames %in% grep(“^C”, ournames, value=TRUE)
- records where the first character is a C
- any record with a value containing a C
- TRUE or FALSE, depending on whether any character in ournames is C
- TRUE or FALSE values, depending on whether the first character in an ournames record is C
Q27. What is the value of names(v)?v <- 1:3names(v) <- c(“a”, “b”, “c”)
v <- 4
Q28. Which of the following statements doesn’t yield the code output below. Review the following code. What is the result of line 3?
x <- c(1, 2, 3, 4)Output:  2 3 4
- x[c(2, 3, 4)]
- x[c(-1, 0, 0, 0)]
- x[c(-1, 2, 3, 4)]
Q29. Given DFMerged <- merge(DF1, DF2) and the image below, how manu rows are in DFMerged?
DF1(data frame 1): DF2(data frame 2):VarA VarB VarA VarD
1 1 2 1 18 212 4 5 2 19 223 7 8 3 20 23
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