Course Outline

Day One

  1. Introduction to R & RStudio (2 hours)
    • Enhancing user-friendliness of R, including available GUIs
    • Overview of RStudio
    • Scripting within RStudio
    • Navigation, sections, and code folding in RStudio
    • Troubleshooting and debugging techniques in RStudio
    • Related software and documentation for government use
    • Accessing help with functions and features
    • Managing projects in RStudio
    • Creating analytical reports using RStudio
    • Utilizing keyboard shortcuts and other useful features
  2. Importing/Exporting Data (1 hour)
    • Flat files – txt, csv
    • Spreadsheet files – xls, xlsx
    • SPSS, SAS, and other data formats
    • Accessing data from SQL data sources
    • Performing SQL database connectivity and operations
  3. Organizing Data (2 hours)
    • Understanding data types and classes
    • Storing data in R – Rdata format
    • Structure of objects in R
    • Working with numbers and vectors
    • Manipulating matrices and tables
    • Handling factors
    • Managing lists
    • Utilizing data frames
    • Working with date and time data
  4. Tabular Representation (3 hours)
    • Overview of packages for data tables – dplyr, tidyr, data.table
    • Using indexes and subscripts
    • Selecting and subsetting observations and variables
    • Filtering and grouping data
    • Performing recoding transformations
    • Reshaping data structures
    • Merging datasets
    • Character manipulation using the stringr package
    • Working with regular expressions

Day Two

  1. Related Software and Documentation (1 hour)
    • Versioning with RStudio and Git for government projects
    • Utilizing Markdown for documentation
    • Creating reports and presentations using LaTeX
    • Developing Shiny web applications
  2. R and Statistics (2 hours)
    • Probability and Normal Distribution
    • Generating random numbers
    • Descriptive statistics for data analysis
    • Standardization and normalization techniques
    • Calculating confidence intervals
    • Conducting hypothesis testing
    • Performing ANOVA (Analysis of Variance)
    • Analyzing qualitative data
  3. Linear Regression (2 hours)
    • Understanding the correlation coefficient and its interpretation
    • Simple and multiple linear regression models
    • Estimation methods – Least squares approach
    • Model validation techniques for assumption violations
    • Variable selection strategies
    • Regularization methods – ridge and lasso regression
    • Generalized least squares for nonlinearity
    • Logistic regression models
  4. Graphical Procedures (2 hours)
    • Creating basic plots for single variables
    • Visualizing relationships between two or more variables
    • Customizing graphical parameters
    • Generating special plots
    • Exporting plots to png, pdf, and jpeg files
    • Extending R's graphical capabilities with ggplot2
  5. Help in R (1 hour)
    • Searching through R documentation for government purposes
    • Exploring R packages and their documentation
    • Utilizing the R Cran Task View to find solutions to problems

Requirements

There are no specific prerequisites required to participate in this course for government professionals.

 14 Hours

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Price per participant

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