• Handled parameters with default values and the ... ellipsis for variable-length arguments
• Used anonymous functions (\\(x) ...) and higher-order functions (Filter, Map, sappl`y)
• Added comments and documentation for clarity
• Designed clean, reusable, well-structured functions

• Imported and organized code effectively using library() and source()
• Used built-in base R functions (e.g., math, date/time, file utilities)
• Created custom scripts for reuse across projects
• Called specific package functions with the :: operator
• Followed best practices for readable and testable code

• Understood common condition types (errors, warnings, messages)
• Used tryCatch() and finally for controlled error management
• Defined custom conditions for domain-specific use cases
• Practiced debugging and robust programming techniques

• BMI Calculator – a simple script (bmi_calculator.R) that computes Body Mass Index (BMI)
• Medication Dosage Calculator – a function that calculates a child’s drug dosage based on weight
• Heart Rate Evaluator – a function that classifies a resting heart rate

• Break big problems into smaller, logical functions
• Group related logic into scripts and eventually packages
• Use if (sys.nframe() == 0) to protect self-test blocks in sourced files

• Anticipate and validate inputs
• Provide clear, actionable error messages
• Catch specific conditions with tryCatch() instead of generic handlers

• Add inline comments explaining purpose and assumptions
• Follow snake_case naming conventions
• Write simple test calls for critical functions

• Multi-file R programs with good structure
• Programs that handle files and user input safely
• Utility scripts that others can source() and use
• Apps with graceful error handling and informative output

You’re ready for Data Analysis with R, where you’ll apply these skills to real-world datasets using powerful packages like:

• dplyr — for data manipulation
• ggplot2 — for visualization
• tidyr — for reshaping data
• Base R statistics and stats package — for hypothesis testing