Data drives most businesses and industries, but only when expressed properly. Data without probability and statistics might as well be an alien language. Probability and statistics allow us to gather insights from data, predict trends, and form data-driven hypotheses about the future.

This skill path introduces the basics of statistical analysis using R, including sampling, working with variables, and understanding frequency distribution tables. Additionally, you’ll learn how to use probability for analysis, and how to create and test hypotheses using significance testing.

  • Use R for statistics sampling, measuring variables, and managing distributions
  • Learn the fundamentals of probability, Bayes' theorem, and the Naive Bayes algorithm
  • Discover how to handle probability density functions and create and support hypotheses

Our students report a median $30k salary increase after learning with Dataquest! Join today!

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What You’ll Learn

In our Probability and Statistics Path, you’ll use R to derive valuable insights from data by building skills like statistical analysis and probability. You’ll begin with the fundamentals of statistics in R. From there, you’ll move onto probability, conditional probability, and hypothesis testing.

After completing our hands-on guided projects and practice problems, you’ll be able to create robust data-driven statistics and analytical predictions. What’s more, you’ll be able to transform raw data into credible and plausible hypotheses for future trends.

Enroll in this skill path if you want to learn how to do the following:

  • Apply statistical fundamentals in R
  • Data sampling and measuring variables
  • Build, visualize, and compare frequency distribution tables
  • Summarize distributions
  • Measure the variability of a distribution
  • Locate and compare values
  • Estimate theoretical and empirical probabilities
  • Assign probabilities based on conditions, event independence, or prior knowledge
  • Handle probability density functions
  • Create testable hypotheses
  • Determine which hypotheses to support from your data
Data Scientist in Python Salary Increase

Average salary for a statistical programmer analyst is $87k/yr, according to Glassdoor.

Data Scientist in Python Job Openings

The Bureau of Labor Statistics predicts 33% job growth for statisticians by 2030.

Data Scientist In Python Job Growth

Facebook, Google, IBM, and many other top tech firms rely on R, according to ListenData.

How Our Probability and Statistics with R Skill Path Works

Learning R for probability and statistics with Dataquest can help you develop the technical and analytical skills you need to translate large and complex datasets into powerful statistics and plausible predictions. Data is everywhere, and it can tell us so much about many different things, but it’s useless if neglected or used improperly. That’s precisely why we’ve created this skill path⁠—to teach you the necessary skills in probability and statistics to make the most of your data.

Demand for data professionals has never been higher, and there’s currently a shortage of people with the skills to process, analyze, and interpret the data collected by virtually every industry, every day.. This path will teach the skills you need to take advantage of the surge in demand, positioning yourself for future job growth.

97% of our learners prefer our unique and interactive teaching method that relies on real-world implementation instead of blind memorization. Because in order to truly gain the in-demand probability and statistics skills hiring managers are looking for, you need to have practical knowledge.

Additionally, you can always count on our thriving community to answer any questions you have and offer a helping hand on a project. Our robust support tools can help guide you through any challenge or roadblock you may come across.

Here’s a quick glance at our Probability and Statistics with R skill path:

  • This skill path consists of the five courses listed below, which cover intermediate and advanced topics about probability and statistics with R.
  • You’ll write real code with dozens of practice problems to validate and apply your skills.
  • At the end of each course, you’ll complete a guided project to reinforce your new knowledge and expand your portfolio.
  • When you complete each course, you’ll receive a certificate that you can share with your professional network.
  •  Once you complete this skill path, you are welcome to try other skill paths that you can add to your toolbelt, like Data Visualization with R or Intermediate Machine Learning with Python.
  • Engage with our friendly community of data professionals, get feedback on your projects, and keep building your skills.

Enroll in this career path to learn R for calculating probability and statistics!

Probability and Statistics with R Skill Path Course List

Statistics Fundamentals in R
Learn about sampling, variables and distributions.

Statistics Intermediate in R: Averages and Variability
Learn how to summarize distributions using the mean, the median, and the mode. Learn to measure variability using variance or standard deviation, and how to locate and compare values using z-scores.

Probability: Fundamentals in R
Learn the fundamentals of probability theory using R.

Conditional Probability in R
Learn about conditional probability, Bayes' theorem, and the Naive Bayes algorithm.

Hypothesis Testing in R
Learn the fundamentals of hypothesis testing using R.

Who Is This Probability and Statistics with R Skill Path for?

Whether you’re simply trying to advance your career by acquiring new skills, you’re just getting started in the data industry, or you’re a student trying to get a head start, you’ll find what you’re looking for in this skill path. No prior knowledge is necessary, so anyone can benefit from the path, especially the following groups:

  • People who want a career as a data analyst or data scientist
  • People seeking a career as a statistician
  • Anyone seeking work with top tech firms like Facebook, Google, and Microsoft
  • People seeking remote work
  • Anyone who works with data in telecommunication, finance, education, and healthcare
  • Junior data scientists or data analysts who want to advance in their current position
  • Anyone who wants to be able to capture, process, and interpret data
  • Anyone who wants to discover how statistics and probabilities work with data
  • Students who want to develop a competitive portfolio
  • Data scientists or data analysts who want to expand the tools at their disposal
  • R users seeking variety in their skills

Qualify for In-demand Jobs in Probability and Statistics

Probability and statistics skills are applicable across many different industries and positions. You can use the skills you’ll learn in this path in the following in-demand data jobs:

  • R programmer
  • Data Scientist
  • Data Analyst
  • Data Architect
  • Geo Statisticians
  • Statistician
  • Statistical Analyst
  • Biostatistician
  • AML Statistician
  • R&D Statistician
  • SAS Programmer
  • Statistical Programmer
  • Predictive Modeler
  • Quantitative Analysis with R
  • Research Data Analyst