R Programming Language Certification Cheat Sheet 2026

The 30 highest-yield R Programming Language Certification facts, distilled from real exam questions. Print it, save it as a PDF, or study it here — free, no sign-up.

1. Which R package provides a unified interface to train and evaluate many machine learning models? → caret
2. In R, which package and function are most commonly used to fit Support Vector Machine (SVM) models? → e1071::svm()
3. Which R package helps enforce column-level data validation rules to catch compliance-breaking data quality issues before analysis? → pointblank
4. Which ggplot2 function changes the overall visual style of a plot (background, grid lines, font)? → theme()
5. Which function performs a two-sample t-test in R? → t.test()
6. What does the predict() function do when called on a fitted lm() model? → Generates predicted values for new or existing data
7. What does the concept of 'data minimization' require when building an R pipeline that processes personal data under GDPR? → Collecting and retaining only the data strictly necessary for the specified purpose
8. Which R function is used to perform a paired t-test when comparing before-and-after measurements on the same subjects? → t.test(x, y, paired = TRUE)
9. Which R function reads a CSV file into a data frame using the readr package? → read_csv()
10. In R, what does the function n() return when used inside summarise()? → The number of rows in each group
11. What argument in geom_bar() or geom_col() maps the fill color to a variable? → fill inside aes()
12. Which R function retrieves the current system time as a POSIXct object? → Sys.time()
13. In R's `qcc` package, what happens when you set `plot=FALSE` in a `qcc()` call? → The control chart object is returned without displaying a plot
14. When communicating uncertainty in a forecast to non-statistician stakeholders, which visualization is most interpretable? → A fan chart or shaded confidence band around the forecast line
15. Which R package provides the `qcc` function for creating Shewhart control charts? → qcc
16. A matrix is a rectangular data collection with ____ dimensions. → 2
17. When publishing a statistical analysis, which action upholds professional data integrity standards? → Reporting all conducted tests, including non-significant results
18. What is the primary purpose of a Define.xml file in a CDISC-compliant regulatory submission created from R analysis datasets? → To describe the structure, contents, and controlled terminology of the submitted datasets
19. Which R package provides tools for working with strings, including pattern matching and string manipulation? → stringr
20. What role does active listening play in R Programming Language Certification practice? → It ensures accurate understanding, demonstrates respect, and improves outcomes
21. In R, which package allows you to create interactive, browser-based visualizations using the Plotly JavaScript library? → plotly
22. Whenever a function is called, ___ suspends execution and switches the part into debug mode. → Both of the above
23. What is reflective practice in R Programming Language Certification professional development? → Systematically examining experiences to gain insight and improve future practice
24. Which operator in R is used to access a function from a package without loading the package? → ::
25. What R syntax should I use to output "Hello World"? → All of the other answers are correct
26. When applying the `demerit()` function in R for weighted defect scoring, what differentiates a 'critical' defect weight from a 'minor' defect weight? → Critical defects receive much higher weights (e.g., 100) vs minor (e.g., 1)
27. Which function computes summary statistics for each group after group_by()? → summarise()
28. How do R Programming Language Certification professionals transfer knowledge from training to practice? → Through supervised practice, mentoring, gradual independence, and ongoing feedback
29. Which dplyr function selects rows based on a condition? → filter()
30. Which R command correctly creates a c-chart for monitoring the number of defects per inspection unit? → qcc(data, type='c')