# 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. # What value does this statement return? `unclass(as.Date("1971-01-01"))` - [ ] 1 - [x] 365 - [ ] 4 - [ ] 12 # What do you use to take an object such as a data frame out of the workspace? - [x] remove() - [ ] erase() - [ ] detach() - [ ] delete() # Review the following code. What is the result of line 3? ``` xvect<-c(1,2,3) xvect[2] <- "2" xvect ``` - [ ] [1] 1 2 3 - [ ] [1] "1" 2 "3" - [x] [1] "1" "2" "3" - [ ] [1] 7 9 # 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)` # 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 # Which choice does R regard as an acceptable name for a variable? - [ ] `Var_A!` - [ ] `\_VarA` - [ ] `.2Var_A` - [x] `Var2_A` # 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. # Which is not a property of lists and vectors? - [ ] type - [ ] length - [ ] attributes - [x] scalar # 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,] # Which function displays the first five rows of the data frame named pizza? - [ ] BOF(pizza, 5) - [ ] first(pizza, 5) - [ ] top(pizza, 5) - [x] head(pizza, 5) # 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) # 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$temperature )` - [x] `class( d.pizza[ , "temperature", drop=F ] )` # What does c contain? ``` a <- c(3,3,6.5,8) b <- c(7,2,5.5,10) c <- a < b ``` - [ ] [1] NaN - [ ] [1] -4 - [ ] [1] 4 -1 -1 2 - [x] [1] TRUE FALSE FALSE TRUE # Review the statements below. Does the use of the dim function change the class of y, and if so what is y's new class? ``` > y <- 1:9 > dim(y) <- c(3,3) ``` - [ ] No, y's new class is "array". - [x] Yes, y's new class is "matrix". - [ ] No, y's new class is "vector". - [ ] Yes, y's new class is "integer". # What is `mydf$y` in this code? `mydf <- data.frame(x=1:3, y=c("a","b","c"), stringAsFactors=FALSE)` - [ ] list - [ ] string - [ ] factor - [x] character vector # 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. # What statement shows the objects on your workspace? - [ ] list.objects() - [ ] print.objects() - [ ] getws() - [x] ls() # What function joins two or more column vectors to form a data frame? - [ ] rbind() - [x] cbind() - [ ] bind() - [ ] coerce() # Review line 1 below. What does the statement in line 2 return? ``` 1 mylist <- list(1,2,"C",4,5) 2 unlist(mylist) ``` - [ ] [1] 1 2 4 5 - [ ] "C" - [x] [1] "1" "2" "C" "4" "5" - [ ] [1] 1 2 C 4 5 # What is the value of y in this code? ``` x <- NA y <- x/1 ``` - [ ] Inf - [ ] Null - [ ] NaN - [x] NA # 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)` # 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),]` # 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() # 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) ``` # 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 # What is the value of names(v[4])? ``` v <- 1:3 names(v) <- c("a", "b", "c") v[4] <- 4 ``` - [x] "" - [ ] d - [ ] NULL - [ ] NA # 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: [1] 2 3 4 ``` - [ ] x[c(2, 3, 4)] - [ ] x[-1] - [ ] x[c(-1, 0, 0, 0)] - [x] x[c(-1, 2, 3, 4)] # Given DFMerged <- merge(DF1, DF2) and the image below, how manu rows are in DFMerged?  - [ ] 6 - [ ] 9 - [ ] 3 - [x] 0 # 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 # 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) # How will R respond to the last line of this code? ``` fact<-factor(c("Rep","Dem","Dem","Rep")) fact [1] Rep Dem Dem Rep Levels: Rep Dem fact[2]<-"Ind" ``` - [ ] > - [ ] [,2]Ind - [x] invalid factor level, NA generated - [ ] Ind # 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 # 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** ```r > newmat [,1] [,2] [1,] 9 25 [2,] 64 16 # The `%*%` operator gives matrix multiplication > mtrx %*% mtrx [,1] [,2] [1,] 49 35 [2,] 56 56 ``` # Which function in R combines different values into a single object? - [ ] connect() - [ ] concat() - [ ] contact() - [x] c() # 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 # 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. # 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) # Which strings could be returned by the function ls(path = "^V")? - [ ] ANOVAData, anovadata - [x] VisitPCA, VarX - [ ] VisitPCA, varx - [ ] Xvar, Yvar # StDf is a data frame. Based on this knowledge, what does this statement return? ```r 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 # Which statement enables you to interactively open a single file? - [ ] file.list() - [ ] file.select() - [x] file.choose() - [ ] file.open() # 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. # What does the `MyMat[ ,3]` subsetting operation return for this code? ```r MyMat = matrix(c(7, 9, 8, 6, 10, 12),nrow=2,ncol=3, byrow = TRUE) ``` - [ ] ``` [ ,3] [1, ] 8 [2, ] 12 ``` - [x] ``` [1] 8 12 ``` - [ ] ``` [1] 10 12 ``` - [ ] ``` [ ,3] [1, ] 10 [2, ] 12 ``` # 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 # Review the statement below. What is the effect of `covariate:factor` on the analysis? ```r 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. ```r # 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 ... ``` # 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 # What is the legitimate name of a data class in R? - [ ] property - [x] integer - [ ] number - [ ] variant # 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)` # `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 # A list named `a` is created using the statement below. Which choice returns TRUE? `a <- list("10", TRUE, 5.6)` - [x] is.list(a[1]) - [ ] is.numeric(a[1]) - [ ] is.logical(a[1]) - [ ] is.character(a[1]) # 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$delivery_min >= 30 which_late <- which(late_delivery) which_late ``` - [ ] ``` late_delivery <- pizza$delivery_min >= 30 late <- piza$late_delivery pizza$late ``` # Which function returns `[1] 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) # Which statement returns the fourth row of a data frame named _fish_? - [x] fish[4, ] - [ ] fish( ,4) - [ ] fish(4, ) - [ ] fish{4, } # What is the value of _csum_? ``` a <- c(1.2, 2, 3.5, 4) b <- c(1.2, 2.2, 3.5, 4) csum <-sum(a == b) ``` - [ ] 8 - [x] 3 - [ ] 0.2 - [ ] 21.6 # A list named _a_ is created using the statement below. Which choice returns TRUE? ``` a <- list("10", TRUE, 5.6) ``` - [x] is.list(a[1]) - [ ] is.numeric(a[1]) - [ ] is.logical(a[1]) - [ ] is.character(a[1])