- Statistics
- R Programming
- Rstudio
- Exploratory Data Analysis
- Statistical Inference
- Statistical Hypothesis Testing
- Linear Regression
- Regression Analysis
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
Offered By
What you will 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
Skills you will gain
About this Specialization
Applied Learning Project
You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions.
No prior experience required.
No prior experience required.
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
There are 3 Courses in this Specialization
Introduction to Probability and Data with R
This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization.
Inferential Statistics
This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data
Linear Regression and Modeling
This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.
Offered by
Duke University
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Frequently Asked Questions
What is the refund policy?
Can I just enroll in a single course?
Is financial aid available?
Can I take the course for free?
Is this course really 100% online? Do I need to attend any classes in person?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
What if I already have a certificate from Data Analysis and Statistical Inference?
Do I need specific software?
More questions? Visit the Learner Help Center.