Enhance your programming skills and delve into statistical analysis with the R programming language. This course covers fundamental concepts, installation, programming structures, data reading, accessing R packages, error handling, and practical data analysis examples.
Throughout the course, you'll learn how to configure statistical programming tools and leverage R functions and error correction tools to gather detailed information using R data frames.
With expert guidance and practical exercises, you'll gain proficiency in R programming, making it an invaluable asset for data analysis and statistical computing.
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This course is divided into four modules, covering essential topics such as installing R, programming structures, error handling, and practical data analysis examples.
Module 1: The first week focuses on the background and practical procedures of R programming. It includes installation on Mac and Windows, configuring R Studio, writing code, and understanding data types. You'll also cover data reading, text data formats, and basic operations.
Module 2: The second week delves into programming using R, covering control structures, creating your own R functions, scope rules, encoding standards, and working with dates and times.
Module 3: Week three explores loop functions and error handling in R. You'll learn about various loop functions and error-checking tools to develop efficient programming solutions.
Module 4: The fourth week emphasizes simulation and profiling. It includes understanding the str function, creating random numbers, simulating linear models, and analyzing data quality.
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