Data Visualization With Ggplot2 — Part 2 MCQs with Explanations

new <- old[-n,] is the correct answer to “Which of the following code will drop the nth column”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

new <- old[,-c(i,j)] is the correct answer to “Which of the following code drop the ith and jth column”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

complete <- subset(data.df,complete.cases(data.df) is the correct answer to “Which of the following statement find cases with no missing values”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

dnorm(x, mean=0, sd=1, log = FALSE) is the correct answer to “Which of the following statement is normal distribution”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

cumsum(x,na=rm=TRUE) is the correct answer to “which of the following statement gives cumulative sum”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

dunif(x, min=0, max=1, log = FALSE) is the correct answer to “Which of the following is uniform distribution”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

as.integer(x) is the correct answer to “Which of the following truncates real x to integers”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

x%in%y is the correct answer to “Which of the following tests each element of x for membership in y”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

max(x, na.rm=TRUE) is the correct answer to “Which of the following finds the maximum value in the vector x, exclude missing values”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

var(x, na.rm=TRUE) is the correct answer to “Which of the following produces the variance covariance matrix”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

rev(x) is the correct answer to “Which of the following will reverse the order of values in x”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

rowMeans(x, na.rm = FALSE, dims = 1) is the correct answer to “Which of the following finds row sums for each level of a grouping variable”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

apply(X, MARGIN, FUN, ...) is the correct answer to “Which of the following statement applies the function (FUN) to either rows (1) or columns (2) on object X”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

apply(x,2,max) is the correct answer to “Which of the following statement finds the maximum for each column”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

which.min(x) is the correct answer to “which of the following statement tells the row with the minimum value for every column”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

solve(A,B) is the correct answer to “Which of the following may be used for linear regression”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

par(omi=c(0,0,1,0) ) is the correct answer to “Which of the following sets the size of the outer margins for the graph”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

hist() is the correct answer to “Which of the following function is used for plotting histogram”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

title( "R language") is the correct answer to “Which of the following will add the title "R language" to the graph”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

plyr is the correct answer to “. . . . . . . . let's you perform SQL queries on your R data frames.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

daply is the correct answer to “. . . . . . . . splits a data frame and results an array (hence the da). Hopefully you're getting the idea here.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

forecast is the correct answer to “. . . . . . . . makes it incredibly easy to fit time series models like ARIMA, ARMA, AR, Exponential Smoothing, etc.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

stringr is the correct answer to “. . . . . . . . provides needed string operators in R.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

install.packages("forecast") is the correct answer to “Which of the following syntax is used to install forecast package”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

lubridate is the correct answer to “Which of the following is similar to Moment.js”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

qcc is the correct answer to “Which of the following is a library for statistical quality control”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

reshape2 is the correct answer to “. . . . . . . . specializes in converting data from wide to long format.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

melt is the correct answer to “. . . . . . . . is used to convert wide data to long data.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

library() is the correct answer to “. . . . . . . . is used to view all packages installed.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

.libPaths() is the correct answer to “. . . . . . . . is used to get library location in R.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

search() is the correct answer to “. . . . . . . . is used to view packages currently loaded.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

abc is the correct answer to “. . . . . . . . contains tools for Approximate Bayesian Computation (ABC).”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

abind is the correct answer to “Which of the following package combine multi-dimensional arrays”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

accelerometry is the correct answer to “Which of the following contains functions for processing uniaxial minute-to-minute accelerometer data”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

avas() is the correct answer to “. . . . . . . . is used for selecting regression transformations.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

adegenet is the correct answer to “Which of the following is an R package for the exploratory analysis of genetic and genomic data”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

aCRM is the correct answer to “. . . . . . . . specializes in functions for analytical Customer Relationship Management.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

bayesclust is the correct answer to “. . . . . . . . searches for significant clusters in genetic data.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

G.S. is the correct answer to “. . . . . . . . Uses Grieg-Smith method on 2 dimensional spatial data.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.

kBestShortestPaths is the correct answer to “. . . . . . . . finds K best paths in a given graph.”. This question is standard in competitive examination syllabi for Data Visualization With Ggplot2.