 Note: Choose the correct answers marked with [x].

R (Programming Language)

Q1. How does a matrix differ from a data frame?

• [ ] A matrix may contain numeric values only.
• [ ] A matrix must not be singular.
• [x] 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?

`unclass(as.Date("1971-01-01"))`

• [ ] 1
• [x] 365
• [ ] 4
• [ ] 12

Q3. What do you use to take an object such as a data frame out of the workspace?

• [x] remove()
• [ ] erase()
• [ ] detach()
• [ ] delete()

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”
• [x]  “1” “2” “3”
• [ ]  7 9

Q5. The variable height is a numeric vector in the code below. Which statement returns the value 35?

• [ ] `height(length(height))`
• [x] `height[length(height)]`
• [ ] `height[length[height]]`
• [ ] `height(5)`

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
• [ ] population
• [ ] trimmed sample
• [x] sample <– not sure

Q7. Which choice does R regard as an acceptable name for a variable?

• [ ] `Var_A!`
• [ ] `\_VarA`
• [ ] `.2Var_A`
• [x] `Var2_A`

Q8. What is the principal difference between an array and a matrix?

• [x] 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?

• [ ] type
• [ ] length
• [ ] attributes
• [x] scalar

Q10. In the image below, the data frame on lines 1 through 4 is named StDf. State and Capital are both factors. Which statement returns the results shown on lines 6 and 7?

• [ ] StDf[1:2,-3]
• [x] StDf[1:2,1]
• [ ] StDf[1:2,]
• [ ] StDf[1,2,]

Q11. Which function displays the first five rows of the data frame named pizza?

• [ ] BOF(pizza, 5)
• [ ] first(pizza, 5)
• [ ] top(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?

• [ ] console(-25)
• [ ] console(reverse=TRUE)
• [ ] history()
• [x] history(max.show = 25)

Q13. d.pizza is a data frame. It’s a column named temperature contains only numbers. If you 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 )`
• [x] `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
• [x]  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”.
• [x] 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)`

• [ ] list
• [ ] string
• [ ] factor
• [x] character vector

Q17. How does a vector differ from a list?

• [ ] Vectors are used only for numeric data, while lists are useful for both numeric and string data.
• [ ] Vectors and lists are the same thing and can be used interchangeably.
• [x] 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?

• [ ] list.objects()
• [ ] print.objects()
• [ ] getws()
• [x] ls()

Q19. What function joins two or more column vectors to form a data frame?

• [ ] rbind()
• [x] cbind()
• [ ] bind()
• [ ] coerce()

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
• [ ] “C”
• [x]  “1” “2” “C” “4” “5”
• [ ]  1 2 C 4 5

Q21. What is the value of y in this code?

``````x <- NA
y <- x/1``````
• [ ] Inf
• [ ] Null
• [ ] NaN
• [x] NA

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(mydata\$(Var1,Var2))`
• [x] `cor.test(mydata\$Var1,mydata\$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)
print(deliver)``````
• [x] `attach(d.pizza)`
• [ ] `summarize(deliver)`
• [ ] `mean <- rbind(d.pizza,count)`
• [ ] `deliver[!complete.cases(deliver),]`

Q24. How to name rows and columns in DataFrames and Matrices F in R?

• [ ] data frame: names() and rownames() matrix: colnames() and row.names()
• [x] 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)
v2<-list(c(4,5,6))
vbound<-cbind(v1,v2)``````
• [ ]
``````v1<-c(1,2,3)
v2<-list(4,5,6))
vbound<-cbind(v1,v2)``````
• [ ]
``````v1<-c(1,2,3)
v2<-c(4,5,6))
vbound<-cbind(v1,v2)``````

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
• [x] TRUE and FALSE values, depending on whether the first character in an ournames record is C

Q27. What is the value of names(v)?

``````v <- 1:3
names(v) <- c("a", "b", "c")
v <- 4``````
• [x] “”
• [ ] d
• [ ] NULL
• [ ] NA

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[-1]
• [ ] x[c(-1, 0, 0, 0)]
• [x] x[c(-1, 2, 3, 4)]

Q29. Given DFMerged <- merge(DF1, DF2) and the image below, how manu rows are in DFMerged?

• [ ] 6
• [ ] 9
• [ ] 3
• [x] 0

Q30. What does R return in response to the final statement?

``````x<-5:8
names(x)<-letters[5:8]
x``````
• [ ] e f g h
“5” “6” “7” “8”
• [ ] 5 6 7 8
• [ ] e f g h
• [x] e f g h
5 6 7 8

Q31. How do you return “October” from x in this code?

``x<-as.Date("2018-10-01")``
• [ ] attr()
• [x] months(x)
• [ ] as.month(x)
• [ ] month(x)

Q32. How will R respond to the last line of this code?

``````fact<-factor(c("Rep","Dem","Dem","Rep"))
fact
 Rep Dem Dem Rep
Levels: Rep Dem
fact<-"Ind"``````
• [ ] >
• [ ] [,2]Ind
• [x] invalid factor level, NA generated
• [ ] Ind

Q33. What does R return?

``````StartDate<- as.Date("2020/2/28")
StopDate<- as.Date("2020/3/1")
StopDate-StartDate``````
• [ ] “1970-01-02”
• [ ] time difference of one day
• [x] time difference of two days
• [ ] error in x-y: nonnumeric argument to binary operator

Q34. What does the expression `mtrx * mtrx` do ?

``````> mtrx <- matrix( c(3,5,8,4), nrow= 2,ncol=2,byrow=TRUE)
> newmat <- mtrx * mtrx``````
• [ ] it transpose mtrx
• [ ] it premultiplies the current netwmat row by the newmat column.
• [ ] it returns the results of a matrix multiplication
• [x] It squares each cell in mtrx
``````> newmat
[,1] [,2]
[1,]    9   25
[2,]   64   16

# The `%*%` operator gives matrix multiplication
> mtrx %*% mtrx
[,1] [,2]
[1,]   49   35
[2,]   56   56``````

Q35. Which function in R combines different values into a single object?

• [ ] connect()
• [ ] concat()
• [ ] contact()
• [x] c()

Q36. Which file contains settings that R uses for all users of a given installation of R?

• [ ] Rdefaults.site
• [ ] Renviron.site
• [x] Rprofile.site
• [ ] Rstatus.site

Q37. If mdf is a data frame, which statement is true ?

• [x] ncol(mdf) equals length(mdf).
• [ ] The number of rows must equals the number of columns.
• [ ] The legnth of any column in mdf may differ from any other column in mdf
• [ ] All columns must have the same data type.

Q38. A list can contain a list as an element. MyList has five columns, and the third column’s item is a list of three items. How do you put all seven values in MyList into a single vector?

• [ ] vector(MyList, length = 7)
• [ ] coerce(MyList, nrows = 1)
• [x] unlist(MyList)
• [ ] coerce(MyList, nrows = 7)

Q39. Which strings could be returned by the function ls(path = “^V”)?

• [x] VisitPCA, VarX
• [ ] VisitPCA, varx
• [ ] Xvar, Yvar

Q40. StDf is a data frame. Based on this knowledge, what does this statement return?

``StDf[, -1]``
• [ ] all but the first row and first column of StDf
• [ ] all but the final column of StDf
• [x] all but the first column of StDf
• [ ] only the first column of StDf

Q41. Which statement enables you to interactively open a single file?

• [ ] file.list()
• [ ] file.select()
• [x] file.choose()
• [ ] file.open()

Q42. How are these data types alike: logical, integer, numeric, and character?

• [ ] Each is a type of data frame.
• [x] Each is a type of atomic vector.
• [ ] Each is a type of complex vector.
• [ ] Each is a type of raw vector.

Q43. What does the `MyMat[ ,3]` subsetting operation return for this code?

``MyMat = matrix(c(7, 9, 8, 6, 10, 12),nrow=2,ncol=3, byrow = TRUE)``
• [ ]
``````[ ,3]
[1, ] 8
[2, ] 12``````
• [x]
`` 8 12``
• [ ]
`` 10 12``
• [ ]
``````[ ,3]
[1, ] 10
[2, ] 12``````

Q44. What does the function `power.anova.test` return?

• [ ] the probability of making a Type I error
• [x] the probability of not making a Type II error
• [ ] the probability of making a Type II error
• [ ] the probability of not making a Type I error

Q45. Review the statement below. What is the effect of `covariate:factor` on the analysis?

``result <- lm(outcome ~ covariate + factor + covariate:factor, data = testcoef)``
• [ ] It forces the intercepts of the individual regressions to zero.
• [x] It calls for the effect of the covariate within each level of the factor.
• [ ] It calls for the effect of each variable from covariate to factor in testcoef.
• [ ] It forces the covariate to enter the equation before the factor levels.
``````# Example call to demonstrate.  `Species` is a Factor.  Petal.Length, Petal.Width are numeric.
# see `help(formula)` for more details on the formula specification.  `:` is "effect modification" or "interaction"

> summary(lm(Petal.Length ~ Petal.Width + Species + Petal.Width:Species, data = iris))
...
Petal.Width:Speciesversicolor   1.3228     0.5552   2.382   0.0185 *
Petal.Width:Speciesvirginica    0.1008     0.5248   0.192   0.8480
...``````

Q46. A variable whose type is numeric can contain which items?

• [ ] integers and real values
• [ ] integers, real, and raw values
• [x] real values only
• [ ] integers, real, and logical values

Q47. What is the legitimate name of a data class in R?

• [ ] property
• [x] integer
• [ ] number
• [ ] variant

Q48. How do you extract the values above the main diagonal from a square matrix named `Rmat`?

• [x] `Rmat[upper.tri(Rmat)]`
• [ ] `upper.triangular(Rmat)`
• [ ] `upper.tri(Rmat)`
• [ ] `upper.diag(Rmat)`

Q49. `x` is a vector of type integer, as shown on line 1 below. What is the type of the result returned by the statement > median(x)?

`x <- c(12L, 6L, 10L, 8L, 15L, 14L, 19L, 18L, 23L, 59L)`

• [ ] numeric
• [ ] integer
• [ ] single
• [x] double

Q50. A list named `a` is created using the statement below. Which choice returns TRUE?

`a <- list("10", TRUE, 5.6)`

• [x] is.list(a)
• [ ] is.numeric(a)
• [ ] is.logical(a)
• [ ] is.character(a)

Q51. How do you obtain the row numbers in a data frame named `pizza` for which the value of `pizza\$delivery_min` is greater than or equal to 30?

• [ ]
``````late_delivery <- pizza\$delivery_min >= 30
index_late <- index(late_delivery)
index_late``````
• [ ]
``````late_delivery <- pizza\$delivery_min >= 30
rownum_late <- rownum(late_delivery)
rownum_late``````
• [x]
``````late_delivery <- pizza\$delivery_min >= 30
which_late <- which(late_delivery)
which_late``````
• [x]
``````late_delivery <- pizza\$delivery_min >= 30
late <- pizaa\$late_delivery
pizza\$late``````

Q52. Which function returns ` TRUE FALSE TRUE`?

`indat <- c("Ash Rd","Ash Cir","Ash St")`

• [ ] grepl(“[Rd|Ave|Dr|St]”, indat)
• [x] grepl(“Rd|Ave|Dr|St”, indat)
• [ ] grepl(“Rd,Ave,Dr,St”, indat)
• [ ] grepl(“[Rd],[Ave],[Dr],[St]”, indat)

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