Dong

“I liked Dataquest because I can control how fast I do the problems. The small scale projects help to make the transition from concepts to the real thing. I wished I had found it earlier.”

Dong Zhou

Senior Scientist @Schrödinger

Path overview

In this path, you’ll learn the foundations of statistics such as sampling, working with variables, and understanding frequency distribution tables and the fundamentals of probability and how to use them for analysis. You’ll also learn how to create and test hypotheses with significance testing, and how to make forecasts based on patterns and trends with real-world data.

Best of all, you’ll learn by doing — you’ll write code and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.

Key skills

  • Cleaning, preparing and analyzing data with R
  • Creating insightful data visualizations
  • Using statistics to perform descriptive analytics
  • Using probabilities to perform predictive analysis

Path outline

Part 1: Probability and Statistics with R [5 courses]

Introduction to Statistics in R 5h

Objectives
  • Sample data using simple random sampling, stratified sampling, and cluster sampling
  • Measure variables in statistics
  • Build, visualize, and compare frequency distribution tables

Intermediate Statistics in R 3h

Objectives
  • Summarize a distribution using the mean, the weighted mean, the median, or the mode
  • Measure the variability of a distribution using the variance and the standard deviation
  • Compare values using z-scores

Introduction to Probability in R 1h

Objectives
  • Estimate theoretical and empirical probabilities
  • Define the fundamental rules of probability
  • Identify combinations and permutations

Conditional Probability in R 2h

Objectives
  • Assign probabilities based on conditions
  • Assign probabilities based on event independence
  • Assign probabilities based on prior knowledge
  • Create spam filters using multinomial Naive Bayes

Hypothesis Testing in R 1h

Objectives
  • Implement probability density functions
  • Create testable hypotheses
  • Decide which hypotheses to support based on your data

The Dataquest guarantee

Guarantee

Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.

Money

We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.

Master skills faster with Dataquest

Go from zero to job-ready

Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build your project portfolio

Build your project portfolio

Build confidence with our in-depth projects, and show off your data skills.

Challenge yourself with exercises

Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Showcase your path certification

Showcase your path certification

Impress employers by completing a capstone project and certifying it with an expert review.

Projects in this path

Guided Project: Investigating Fandango Movie Ratings

Learn to combine the skills you learned in this course to perform practical data analysis.

Guided Project: Finding the Best Markets to Advertise In

Learn to combine the skills you learned in this course to perform practical data analysis.

Guided Project: Mobile App for Lottery Addiction

Learn to use probability and combinatorics in a practical setting.

Guided Project: Building a Spam Filter with Naive Bayes

Learn to use conditional probability and Naive Bayes in a practical setting.

Guided Project: Winning Jeopardy

Learn how to analyze text while figuring out strategies to win at Jeopardy.

Plus 0 more projects

Build your project portfolio with the Data Analyst in Python path.

Grow your career with
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Aaron

Aaron Melton

Business Analyst at Aditi Consulting

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”

Jessi

Jessica Ko

Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”

Victoria

Victoria E. Guzik

Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

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