R Programming Language Certification — Questions and Answers

Question 1: What is the primary purpose of the `rvest` package in R?

Sending HTTP POST requests to REST APIs
Managing browser cookies and sessions
Web scraping and parsing HTML/XML content (Correct answer)
Generating HTML reports from R Markdown

Correct answer: Web scraping and parsing HTML/XML content

The rvest package provides tools for web scraping, allowing R users to read HTML pages and extract structured data using CSS selectors or XPath expressions.

Question 2: What is the primary purpose of regulatory compliance in R Programming Language Certification practice?

To create bureaucratic burden
To benefit regulators only
To protect public safety, ensure quality standards, and maintain professional accountability (Correct answer)
To limit competition

Correct answer: To protect public safety, ensure quality standards, and maintain professional accountability

This is fundamental to R Programming Language Certification practice. To protect public safety, ensure quality standards, and maintain professional accountability represents the professional standard for regulatory in the R Programming Language Certification certification framework.

Question 3: A finance stakeholder needs a table of summary statistics. Which R package produces publication-quality tables directly from data frames most efficiently?

kableExtra or gt (Correct answer)
cat()
writeLines()
base print()

Correct answer: kableExtra or gt

kableExtra and gt provide rich formatting options—column alignment, highlighting, footnotes—that turn R data frames into professional HTML or LaTeX tables.

Question 4: Which ggplot2 function controls the color palette for a discrete variable?

theme_color()
palette_discrete()
geom_color()
scale_fill_manual() (Correct answer)

Correct answer: scale_fill_manual()

scale_fill_manual() allows manual specification of fill colors for discrete variables by providing a named vector of color values.

Question 5: What is the first step in risk assessment for R Programming Language Certification professionals?

Implementing controls immediately
Delegating to others
Identifying potential hazards and vulnerabilities in the specific context (Correct answer)
Purchasing insurance

Correct answer: Identifying potential hazards and vulnerabilities in the specific context

This is fundamental to R Programming Language Certification practice. Identifying potential hazards and vulnerabilities in the specific context represents the professional standard for risk management in the R Programming Language Certification certification framework.

Question 6: Which R function performs a Wilcoxon rank-sum test (non-parametric equivalent of t-test)?

mann.whitney()
wilcox.test() (Correct answer)
nonpar.test()
ranksum()

Correct answer: wilcox.test()

wilcox.test() performs both the Wilcoxon signed-rank test (one-sample/paired) and the Wilcoxon rank-sum (Mann-Whitney) test for two independent samples.

Question 7: A data journalist wants to create a choropleth map of US state unemployment rates using ggplot2. After joining unemployment data to a spatial data frame, which geom renders filled polygons for each state?

geom_map(aes(map_id=state, fill=unemployment_rate))
geom_polygon(aes(fill=unemployment_rate))
geom_sf(aes(fill=unemployment_rate)) (Correct answer)
geom_tile(aes(fill=unemployment_rate))

Correct answer: geom_sf(aes(fill=unemployment_rate))

geom_sf() renders simple features (sf) spatial objects and respects their geometry automatically, making it the modern standard for maps in ggplot2.

Question 8: When running `gage.rr()` in R's `SixSigma` package, a %Contribution of measurement system above what threshold is generally considered unacceptable?

5%
10%
30% (Correct answer)
50%

Correct answer: 30%

A measurement system %Contribution (or %Study Variation) above 30% is generally unacceptable; below 10% is acceptable; 10–30% may be acceptable depending on context.

Question 9: In R, what is the primary purpose of Western Electric (WECO) rules applied via `qcc`?

To calculate control limits using 2-sigma instead of 3-sigma bounds
To normalize non-Gaussian process data before charting
To detect non-random patterns beyond just points outside control limits (Correct answer)
To set the AQL for acceptance sampling plans

Correct answer: To detect non-random patterns beyond just points outside control limits

WECO rules detect non-random patterns (runs, trends, stratification) within control limits that a single 3-sigma rule alone would miss.

Question 10: In ggplot2, which function sets fixed x and y axis limits on a plot?

xlim() and ylim() (Correct answer)
coord_range()
set_limits()
axis_range()

Correct answer: xlim() and ylim()

xlim() and ylim() (or limits= inside scale_x/y_continuous()) set the visible range of each axis in ggplot2.

Question 11: In R, `lavaan::sem()` is used for which type of analysis common in social science research?

Spatial estimation modeling
Sequential experimental modeling
Survival analysis
Structural Equation Modeling (Correct answer)

Correct answer: Structural Equation Modeling

The lavaan package's sem() function fits Structural Equation Models, allowing simultaneous estimation of multiple relationships.

Question 12: What does the aes() function do in ggplot2?

Defines aesthetic mappings between data variables and visual properties (Correct answer)
Exports plots to files
Adjusts axis scales
Sets color themes

Correct answer: Defines aesthetic mappings between data variables and visual properties

aes() (aesthetic mappings) maps data variables to visual properties like x, y, color, size, and shape.

Question 13: In the context of R-based financial modeling subject to SOX compliance, what is the primary purpose of maintaining version control for R scripts?

To speed up code execution on production servers
To provide an auditable change history satisfying internal control requirements (Correct answer)
To enable parallel processing across multiple cores
To automatically detect syntax errors before runtime

Correct answer: To provide an auditable change history satisfying internal control requirements

SOX (Sarbanes-Oxley) requires auditable evidence of internal controls; version control systems like Git provide a timestamped, attributed history of every code change.

Question 14: Which function computes summary statistics for each group after group_by()?

aggregate()
summarise() (Correct answer)
reduce()
collapse()

Correct answer: summarise()

summarise() (or summarize()) computes one or more summary statistics for each group defined by group_by().

Question 15: What argument in geom_bar() or geom_col() maps the fill color to a variable?

fill inside aes() (Correct answer)
hue= argument
color= argument
palette= argument

Correct answer: fill inside aes()

Mapping fill inside aes(), e.g. aes(fill = variable), assigns bar fill colors based on a data variable.

Question 16: Which function in R is used to perform a Wilcoxon rank-sum test (non-parametric alternative to t-test)?

nonpar.test()
kruskal.test()
wilcox.test() (Correct answer)
rank.test()

Correct answer: wilcox.test()

wilcox.test() performs the Wilcoxon rank-sum (Mann-Whitney) test or Wilcoxon signed-rank test for non-normal data.

Question 17: Which ggplot2 function allows you to arrange multiple separate plots in a grid layout?

patchwork or gridExtra (Correct answer)
layout()
par(mfrow=)
facet_grid()

Correct answer: patchwork or gridExtra

The patchwork package and gridExtra's grid.arrange() are commonly used to combine separate ggplot2 plots into one figure.

Question 18: What is a compliance management system in R Programming Language Certification practice?

A structured framework of policies, procedures, and controls that ensure regulatory adherence (Correct answer)
A government reporting requirement
An optional business tool
A software application only

Correct answer: A structured framework of policies, procedures, and controls that ensure regulatory adherence

This is fundamental to R Programming Language Certification practice. A structured framework of policies, procedures, and controls that ensure regulatory adherence represents the professional standard for regulatory in the R Programming Language Certification certification framework.

Question 19: In R, the `evd` package function `fpot()` is used to fit which model relevant to tail risk?

ARMA model for volatility
Peaks Over Threshold (POT) using the Generalized Pareto Distribution (Correct answer)
Normal mixture model
Logistic regression for default

Correct answer: Peaks Over Threshold (POT) using the Generalized Pareto Distribution

`fpot()` fits a Generalized Pareto Distribution to exceedances over a chosen threshold, central to Peaks-Over-Threshold analysis.

Question 20: The statements in the following program will be executed in the following order: Line 1: print (''welcome'') Line 2: printHello <- function() { Line 3: print(''Hello'') Line 4: } Line 5: printHello() Line 6: print(''done'')

1, 2, 3, 4, 5, 6
1, 5, 2, 3, 4, 6 (Correct answer)
5, 6, 1, 2, 3, 4
1, 2, 5, 6, 3, 4

Correct answer: 1, 5, 2, 3, 4, 6

R executes code sequentially. Line 1 prints immediately. Lines 2-4 define the function `printHello`, but the code inside the function body (Line 3) is not executed until the function is called. Line 5 calls `printHello()`, causing Line 3 to execute. Finally, Line 6 executes after the function call completes.

Question 21: In R, what is the correct way to perform a multi-variate control chart (T² chart) for monitoring two correlated quality characteristics simultaneously?

T2chart(data, vars=c('x','y'))
mqcc(data, type='T2') (Correct answer)
qcc(data, type='multivariate')
hotellingT2(data)

Correct answer: mqcc(data, type='T2')

`mqcc()` from the `qcc` package handles multivariate quality control, with `type='T2'` specifying the Hotelling T² control chart for correlated variables.

Question 22: Which dplyr function removes duplicate rows from a data frame?

dedupe()
unique_rows()
filter_unique()
distinct() (Correct answer)

Correct answer: distinct()

distinct() returns only unique rows from a data frame, optionally based on specified columns.

Question 23: Which R package is most widely used for creating layered, publication-quality graphics?

plotly
base graphics
lattice
ggplot2 (Correct answer)

Correct answer: ggplot2

ggplot2 implements the Grammar of Graphics, allowing users to build complex, publication-quality plots by layering geometric objects and aesthetics.

Question 24: R language's apply function requires __ arguments

3
4 (Correct answer)
1
5

Correct answer: 4

The `apply()` function in R is designed to apply a function to the margins (rows or columns) of a matrix or array. Its standard signature is `apply(X, MARGIN, FUN, ...)`, meaning it requires at least three arguments: the array/matrix `X`, the `MARGIN` (1 for rows, 2 for columns), and the `FUN`ction to apply. The `...` allows for passing additional arguments to `FUN`, making it a fourth conceptual argument slot.

Question 25: What does the dplyr function group_by() do?

Groups rows for subsequent summarise operations (Correct answer)
Merges two data frames
Removes duplicate rows
Sorts rows by a column

Correct answer: Groups rows for subsequent summarise operations

group_by() defines groups within a data frame so that subsequent operations like summarise() are applied to each group separately.

Question 26: Which R package is most widely used for creating advanced data visualizations based on the Grammar of Graphics?

base graphics
ggplot2 (Correct answer)
plotly
lattice

Correct answer: ggplot2

ggplot2, created by Hadley Wickham, implements the Grammar of Graphics and is the most popular R visualization package.

Question 27: Which function adds axis labels and a title to a ggplot2 plot?

axis_labels()
annotate()
title()
labs() (Correct answer)

Correct answer: labs()

labs() sets plot labels including title, subtitle, caption, and axis labels (x, y) in a single concise function call.

Question 28: What does the aes() function define in ggplot2?

Theme settings
Plot colors and fonts
Axis labels and titles
Aesthetic mappings between data variables and visual properties (Correct answer)

Correct answer: Aesthetic mappings between data variables and visual properties

aes() (aesthetics) maps data variables to visual properties like x/y position, color, size, and shape in a ggplot2 plot.

Question 29: Which ggplot2 function call adds a clear, descriptive title and axis labels to a plot before sharing with stakeholders?

ggtitle() only
annotate()
xlab() and ylab() only
labs(title = '...', x = '...', y = '...') (Correct answer)

Correct answer: labs(title = '...', x = '...', y = '...')

labs() is the unified ggplot2 function for setting title, subtitle, caption, and all axis labels in a single, readable call.

Question 30: Which R package provides tools for cross-validation and training machine learning models with a unified interface?

mlr
tidymodels
caret (Correct answer)
scikit

Correct answer: caret

caret (Classification And REgression Training) provides a unified interface for training, tuning, and evaluating hundreds of ML models.

Question 31: Which R function serializes an R object to a binary format for saving to disk?

dump()
write.csv()
dput()
saveRDS() (Correct answer)

Correct answer: saveRDS()

saveRDS() saves a single R object to a binary .rds file that can be restored with readRDS().

R Programming Language Certification

The R Programming Language Certification validates proficiency in statistical computing, data manipulation, visualization, and practical R programming skills used across data science and analytics workflows.

Questions

35 min

Time Limit

70%

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