Podcast
Questions and Answers
What is the primary textbook for this course?
What is the primary textbook for this course?
R for Data Science (2e), 2023
Which formats will the lectures and labs use?
Which formats will the lectures and labs use?
The console is located in the upper half of the interface.
The console is located in the upper half of the interface.
False
Which of the following keyboard shortcuts adds a code block?
Which of the following keyboard shortcuts adds a code block?
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What should you learn to read for help in R?
What should you learn to read for help in R?
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What action does clicking the 'Knit' button perform?
What action does clicking the 'Knit' button perform?
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The keyboard shortcut Cmd/Ctrl+S is used for ______.
The keyboard shortcut Cmd/Ctrl+S is used for ______.
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Study Notes
Course and R Introduction
- This course will explore data science using real data and the R programming language.
- The syllabus outlines course policies and expectations.
- It is recommended to use both the 2nd edition of "R for Data Science" and "Tidy Modeling with R" as primary resources.
- The course will cover most of the 2nd edition of "R for Data Science", but not in the exact order presented in the book.
- This course focuses on using R and the tidyverse packages. We will primarily follow the 2nd edition of "R for Data Science" which is more up-to-date.
- The course uses both Quarto and R Markdown for code and document development.
- Both Quarto (.qmd) and R Markdown (.Rmd) files are similar in functionality with minor differences.
- Quarto will be used for lectures, and R Markdown will be used for labs and assignments.
- Take the lecture files as templates and explore further details in the respective books.
- Read chapters 29.3 in the 2nd edition and 27 in the 1st edition for further understanding of Quarto and R Markdown respectively.
- Familiarize yourself with the RStudio interface and the basics of running scripts and starting projects by reading Chapter 7 in the 2nd edition.
- Use the Visual editor in RStudio for editing both Rmd and qmd files.
- In RStudio, the Source file can be edited similar to any text file, and there are useful keyboard shortcuts, such as Cmd/Ctrl+C, Cmd/Ctrl+V, Cmd/Ctrl+S, Cmd/Ctrl+Alt+I, Cmd/Ctrl+Shift+Enter, and Cmd/Ctrl+Shift+P.
- Utilize the Console, located in the lower half of RStudio, for testing and debugging code before incorporating it into files.
- Use the "?" function in the Console to access the help documentation.
- Click the Render button (for .qmd files) or the Knit button (for .Rmd files) to generate a document with code and output.
- Code blocks can be run separately by clicking the arrow button or the Run button in the upper right corner.
Effective Learning Approach
- Read the method book completely.
- Play the song through once as written.
- Ask for assistance if needed, and move on to the next song if the information makes sense.
- It's important to read and play through the material, and not just rely on asking questions.
- Practice slowly, repeat challenging sections, and play similar songs or scales to solidify your understanding.
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Description
This quiz covers the fundamentals of data science using the R programming language, as outlined in the course syllabus. Students will explore course policies, resources like 'R for Data Science', and practical applications using Quarto and R Markdown. Test your understanding of the materials and expectations for this data science course.
