Statistics and R Programming

By: Harvard University
Free
Intermediate,
Duration: 4 Weeks

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

Learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation.

Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses.

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Course ByInstructor
Harvard UniversityRafael Irizarry, Michael Love

Course Details

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you.

If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures.

Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.



What you will learn?

  • Random variables
  • Distributions
  • Inference: p-values and confidence intervals
  • Exploratory Data Analysis
  • Non-parametric statistics

Other Details

Course Instructors

Rafael Irizarry: Professor of Biostatistics, T.H. Chan School of Public Health
Michael Love: Assistant Professor, Departments of Biostatistics and Genetics, UNC Gillings School of Global Public Health

Check Course Content, Faqs, Rating and other important information about this course.

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Disclaimer

We have tried to provide the best updated information about this Statistics and R Programming course. However, if you find this course is not available or if there are any changes to this free course of Statistics and R Programming then do let us know. Our team will make the necessary changes.



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