R Programming Quiz: Assess Your Skill Level

Written by Coursera • Updated on

Test your R programming skills with this quick assessment. Answer 10 multiple-choice questions to get your score, then check the Scoring Guide to find your level and recommended learning path.

R Programming Quiz

R programming is one of the skills employers in the data science industry most frequently request. It is a powerful and versatile language primarily used in data analysis, statistics, and data science. R programming has become essential for professionals in these fields, offering robust tools for statistical modeling and data visualization. With its ability to handle large datasets and perform complex analyses, R has gained significant popularity across healthcare, finance, and marketing industries. Its key features, such as a wide range of libraries and packages, make it highly flexible and efficient.

Answer the following skill-based R programming questions and click Submit to calculate your score. Use your score to find recommendations that align with your current skill level and explore career paths that interest you.

Test Structure

  • 10 multiple-choice questions

  • Takes approximately 5-10 minutes

  • Immediate results with career recommendations

  • Custom learning paths based on results

1. What is the correct way to create a vector in R?

array(1, 2, 3)
c(1, 2, 3)
vector(1, 2, 3)
list(1, 2, 3)

2. Which function would you use to remove missing values from a dataset?

remove.na()
delete.na()
na.omit()
clear.na()

3. What does the pipe operator %>% do in R?

Concatenates strings
Passes the output of one function as input to another
Creates a logical OR condition
Performs matrix multiplication

4. Which package would you use for data visualization?

dataviz
ggplot2
visualize
plot

5. What is the difference between a list and a data frame?

Lists can contain different data types, data frames must have same type per column
Lists are one-dimensional, data frames are two-dimensional
There is no difference
Lists can only contain numbers

6. Which function would you use for linear regression?

regression()
linear.model()
lm()
linreg()

7. What does this code do?

mtcars %>%
  group_by(cyl) %>%
  summarise(mean_mpg = mean(mpg))
  
Calculates total MPG by cylinder
Calculates average MPG for each cylinder group
Counts cars by cylinder
Lists all cars with their MPG

8. What is the purpose of lapply()?

To apply a function to each element of a list
To create a list
To combine lists
To sort a list

9. Which statement about factors in R is correct?

They can only contain numbers
They are used to represent categorical data
They cannot be ordered
They are the same as characters

10. What does the tidyr package primarily do?

Cleans data
Reshapes data between wide and long formats
Creates plots
Performs statistical tests

Scoring Guide & Course Recommendations

Your quiz score above aligns with a general proficiency level of beginner, intermediate, or advanced. Match your score to the ranges below and explore the recommended course.

0-30: Beginner Level

40-70: Intermediate Level

80-100: Advanced Level

Skills Covered by Level

As you progress in your R programming career, different levels have different skills, and here are some common ones.

Beginner Level

  • Basic syntax

  • Data types and structures

  • Basic functions

  • Simple data manipulation

  • Basic plotting

  • Reading/writing data

Intermediate Level

  • Data wrangling with tidyverse

  • Statistical analysis

  • Advanced visualization

  • Package usage

  • Basic modeling

  • Data cleaning

Advanced Level

  • Machine learning

  • Advanced statistics

  • Package development

  • Production deployment

  • Performance optimization

  • Complex data analysis

Career Paths

Your R programming career path will be unique to your strengths and interests. Below are some common roles at different skill levels. Explore our Web Development Career: Decision Tree to understand better how your R programming skills can take your career in an exciting direction.

You can start programming in R today by enrolling in a beginner-focused online course like Data Analysis with R Programming. Led by Google, you’ll explore fundamental concepts like functions, variables, and data types. Additionally, you can gain insights into performing basic formatting with R Markdown and generate visualizations in R.

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