Code and run your first R program in minutes without installing anything! The "Data Analysis in R with RStudio & Tidyverse" course is designed for learners with no prior coding experience, providing foundational knowledge of data analysis in R. The course covers descriptive statistics, importing and wrangling data, and using statistical tests to compare populations and describe relationships.
This course presents examples in R using the industry-standard Integrated Development Environment (IDE) RStudio. You'll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks to small, approachable coding exercises that take minutes instead of hours. Finally, a cumulative lab at the end of the course will provide you an opportunity to apply all learned concepts within a real-world context.
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This course comprises five modules covering descriptive statistics, data import and manipulation, statistical tests for comparing populations, relationships between data sets, and a cumulative lab for real-world application.
Gain foundational knowledge in describing numerical data sets using statistical functions in R. Learn to apply statistical functions to analyze and understand numerical data, providing a strong basis for further data analysis.
Explore the process of importing and describing mixed data sets using Tidyverse. Learn to manipulate and summarize mixed data sets effectively, preparing them for further analysis and interpretation.
Discover how to use statistical tests to compare populations and determine differences. Learn to apply appropriate statistical tests and interpret the results, gaining insights into population comparisons.
Understand how to use statistical tests to describe and explain relationships between data sets. Learn to identify and analyze relationships, providing valuable insights for data interpretation and decision-making.
Apply all learned concepts within a real-world context in the R Data Analysis Lab. Gain practical experience in data analysis by solving real-world problems and solidify your understanding of data analysis in R.
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Learn how to import various types of data into R, including CSV files, Excel files, web data, and relational databases in this hour-long guided project.
Learn the fundamentals of relational databases using MySQL in this guided project. Gain essential SQL querying skills and database manipulation techniques.