In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.
Data Analysis with R Specialization
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Data Analysis with R Specialization
Master Data Analysis with R. Statistical mastery of data analysis including basic data visualization, statistical testing and inference, and linear modeling
Instructor: Mine Çetinkaya-Rundel
159,791 already enrolled
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Get in-depth knowledge of a subject
(6,032 reviews)
Beginner level
No prior experience required
4 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(6,032 reviews)
Beginner level
No prior experience required
4 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Analyze and visualize data
Perform hypothesis tests, interpret statistical results (e.g., p-values), and report the results of your analysis to clients
Fit, examine, and utilize regression models to examine relationships between multiple variables
Install and use R and RStudio
Overview
Skills you'll gain
- Exploratory Data Analysis
- Statistics
- Probability
- Statistical Reporting
- Bayesian Statistics
- Regression Analysis
- Correlation Analysis
- Descriptive Statistics
- Statistical Modeling
- Statistical Methods
- Data Analysis
- Probability Distribution
- Statistical Hypothesis Testing
- Statistical Analysis
- Statistical Inference
- Probability & Statistics
- Data Visualization
- Sampling (Statistics)
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
31 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Duke University
Specialization - 3 course series
What you'll learn
Skills you'll gain
Category: Data Analysis
Category: Probability
Category: R Programming
Category: Descriptive Statistics
Category: Probability Distribution
Category: Statistical Inference
Category: Sampling (Statistics)
Category: Statistical Software
Category: Statistical Analysis
Category: Exploratory Data Analysis
Category: Bayesian Statistics
Category: Statistics
What you'll learn
Skills you'll gain
Category: Statistical Inference
Category: Statistical Hypothesis Testing
Category: Sampling (Statistics)
Category: Data Analysis
Category: Statistical Methods
Category: R Programming
Category: Statistical Analysis
Category: Statistical Reporting
Category: Probability & Statistics
Category: Probability Distribution
Category: Software Installation
Category: Statistical Software
What you'll learn
Skills you'll gain
Category: Regression Analysis
Category: Statistical Modeling
Category: Predictive Modeling
Category: Correlation Analysis
Category: Mathematical Modeling
Category: R Programming
Category: Statistics
Category: Exploratory Data Analysis
Category: Statistical Inference
Category: Statistical Methods
Category: Data Analysis
Category: Statistical Analysis
Category: Anomaly Detection
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Frequently asked questions
Basic math, no programming experience required. A genuine interest in data analysis is a plus!
In the later courses in the Specialization, we assume knowledge and skills equivalent to those which would have been gained in the prior courses (for example: if you decide to take course four, Bayesian Statistics, without taking the prior three courses we assume you have knowledge of frequentist statistics and R equivalent to what is taught in the first three courses).
Yes.
Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
More questions
Financial aid available,