An introductory course that teaches the foundations of scientific and statistical programming using R software.
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Understand how to create and manipulate R data structures used in scientific programming applications.
Understand and use important statistical R programming concepts such as looping and control structures, interactive data input and formatting output, writing functions as programs, writing output to a file and plotting output.
Understand and be able to use the R apply family of functions efficiently.
Know how to debug programs and how to make programs run more efficiently.
Understand and be able to implement various resampling methods effectively, including bootstrapping, jackknifing and N-fold cross validation.
This comprehensive Programming Statistical Applications in R curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
What you need before starting this Programming Statistical Applications in R course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Geoffrey Hubona, Ph.D.
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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