Introduction to Programming and Plotting with R
Master R programming fundamentals through hands-on workshops using RStudio Cloud. Learn data structures, tidyverse data manipulation, and ggplot2 visualization through research-focused exercises. Perfect for researchers with no prior programming experience.
Workshop Description
This comprehensive 3-day workshop introduces researchers to R programming through practical, hands-on exercises using RStudio Cloud. No prior programming experience is required - we start from the absolute basics and build up to sophisticated data analysis and visualization skills essential for modern research.
You'll learn fundamental R concepts including variables, vectors, data frames, control structures, and functions, then apply these skills to analyze real research datasets using the tidyverse ecosystem. The workshop emphasizes reproducible research practices, statistical thinking, and creating publication-quality visualizations with ggplot2.
By the end of this workshop, you'll be comfortable working with R scripts and R Markdown documents, manipulating complex datasets, creating stunning visualizations, and conducting basic statistical analyses. All materials and datasets are provided, and you'll leave with practical skills you can immediately apply to your research projects.
Instructor
Course Fee
$299.0
Maximum Seats
20
Duration
3 half-days
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Time
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A comprehensive 3-day journey from R basics to advanced data visualization and analysis
Format: Each day is approximately 4 hours with hands-on exercises using RStudio Cloud
Prerequisites: No prior programming experience required. You'll need internet access to use RStudio Cloud and basic computer literacy
What you'll learn: Core R programming concepts, data manipulation with tidyverse, creating publication-quality plots with ggplot2, basic statistical analysis, and reproducible research with R Markdown
Materials provided: All datasets, R scripts, and resources will be provided. You'll have lifetime access to all workshop materials and code templates
Day 1: R Fundamentals & Data Structures
Master the basics of R programming and data organization
Welcome & RStudio Setup (30 min): Workshop overview, RStudio Cloud introduction, understanding the interface (console, script editor, environment, plots), and saving projects
R Basics & Variables (45 min): Basic syntax, assignment operators, data types (numeric, character, logical), and variable naming conventions for research
Vectors & Data Structures (1 hr): Creating and manipulating vectors, indexing and subsetting, lists for complex data, and understanding R's vectorized operations
Data Frames (1 hr): Creating data frames, importing CSV files, exploring structure with str() and summary(), accessing columns and rows, and basic data inspection techniques
Getting Help & Functions (45 min): Using R's help system, understanding function syntax, common base R functions, and troubleshooting errors
Day 2: Data Manipulation with Tidyverse
Learn modern R data manipulation and transformation techniques
Introduction to Tidyverse (30 min): Understanding the tidyverse philosophy, loading packages with library(), and the pipe operator (%>%) for readable code
Data Import & Exploration (45 min): Reading various file formats with readr, initial data exploration with glimpse() and summary(), and handling common import issues
Data Manipulation with dplyr (1.5 hrs): Essential verbs: select() for columns, filter() for rows, mutate() for new variables, arrange() for sorting, and summarise() with group_by() for aggregations
Data Reshaping with tidyr (45 min): Wide vs long data formats, pivot_longer() and pivot_wider() for data restructuring, and handling missing values
Combining Datasets (30 min): Joining data frames with left_join(), inner_join(), and understanding relational data concepts
Day 3: Data Visualization & Reproducible Research
Create publication-quality plots and learn reproducible research practices
Introduction to ggplot2 (1 hr): Grammar of graphics philosophy, aesthetic mappings, geometric objects (geoms), and building plots layer by layer
Advanced Plotting (1.5 hrs): Customizing plots with scales, themes, and colors, creating faceted plots, adding statistical summaries, and exporting high-resolution figures for publications
R Markdown Fundamentals (1 hr): Creating reproducible reports, combining code and text, formatting with markdown syntax, and rendering to HTML and PDF formats
Mini-Project & Best Practices (30 min): Complete analysis workflow from data import to final report, organizing R projects, version control basics, and sharing reproducible research
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