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Course Outline
Day 1
Introduction and Preliminaries for Government
- Making R more user-friendly, including available GUIs
- RStudio
- Related software and documentation
- R and statistics for government applications
- Using R interactively in a public sector context
- An introductory session for government users
- Getting help with functions and features for government tasks
- R commands, case sensitivity, etc., tailored for government workflows
- Recall and correction of previous commands in a public sector environment
- Executing commands from or diverting output to a file for government reporting
- Data permanency and removing objects for efficient government data management
Simple Manipulations; Numbers and Vectors
- Vectors and assignment in government datasets
- Vector arithmetic for public sector analysis
- Generating regular sequences for government reports
- Logical vectors for data validation in the public sector
- Handling missing values in government databases
- Character vectors for textual data in government records
- Index vectors; selecting and modifying subsets of a dataset for government use
- Other types of objects relevant to government operations
Objects, Their Modes and Attributes
- Intrinsic attributes: mode and length in government data
- Changing the length of an object for efficient government data handling
- Getting and setting attributes for government datasets
- The class of an object in a public sector context
Ordered and Unordered Factors
- A specific example for government applications
- The function tapply() and ragged arrays in government data analysis
- Ordered factors for structured government datasets
Arrays and Matrices
- Arrays for government data representation
- Array indexing. Subsections of an array for detailed government reports
- Index matrices for complex government data manipulation
- The array() function
- Mixed vector and array arithmetic. The recycling rule in government datasets
- The outer product of two arrays for comprehensive government analysis
- Generalized transpose of an array for versatile government data use
- Matrix facilities
- Matrix multiplication for government models
- Linear equations and inversion in government calculations
- Eigenvalues and eigenvectors for advanced government analysis
- Singular value decomposition and determinants for robust government data processing
- Least squares fitting and the QR decomposition for accurate government predictions
- Forming partitioned matrices, cbind() and rbind() for government data organization
- The concatenation function, (), with arrays for streamlined government data handling
- Frequency tables from factors for government reporting
Day 2
Lists and Data Frames for Government
- Lists in government datasets
- Constructing and modifying lists
- Concatenating lists for comprehensive government data
- Data frames for efficient government data management
- Making data frames from government records
- attach() and detach() for managing government datasets
- Working with data frames in a public sector context
- Attaching arbitrary lists for versatile government data use
- Managing the search path for government data retrieval
Data Manipulation for Government
- Selecting, subsetting observations and variables in government datasets
- Filtering, grouping for targeted government analysis
- Recoding, transformations for accurate government data representation
- Aggregation, combining data sets for comprehensive government reporting
- Character manipulation, stringr package for textual government data
Reading Data for Government
- Txt files for government records
- CSV files for government data exchange
- XLS, XLSX files for government spreadsheets
- SPSS, SAS, Stata, and other formats data for government interoperability
- Exporting data to txt, csv, and other formats for government sharing
- Accessing data from databases using SQL language for government data integration
Probability Distributions for Government
- R as a set of statistical tables for government analysis
- Examining the distribution of a set of data in a public sector context
- One- and two-sample tests for government hypothesis testing
Grouping, Loops, and Conditional Execution for Government
- Grouped expressions for structured government data processing
- Control statements
- Conditional execution: if statements for decision-making in the public sector
- Repetitive execution: for loops, repeat, and while for automated government tasks
Day 3
Writing Your Own Functions for Government
- Simple examples for government applications
- Defining new binary operators for specialized government functions
- Named arguments and defaults for flexible government data handling
- The '...' argument for versatile government function parameters
- Assignments within functions for efficient government data processing
- More advanced examples
- Efficiency factors in block designs for government projects
- Dropping all names in a printed array for clear government reports
- Recursive numerical integration for complex government analysis
- Scope for managing government data environments
- Customizing the environment for tailored government workflows
- Classes, generic functions, and object orientation for structured government data management
Statistical Analysis in R for Government
- Linear regression models for government predictions
- Generic functions for extracting model information for government reporting
- Updating fitted models for ongoing government analysis
- Generalized linear models
- Families for diverse government data types
- The glm() function for advanced government modeling
- Classification
- Logistic Regression for government decision support
- Linear Discriminant Analysis for government classification tasks
- Unsupervised learning
- Principal Components Analysis for government data reduction
- Clustering Methods (k-means, hierarchical clustering, k-medoids) for government segmentation
- Survival analysis
- Survival objects in R for government studies
- Kaplan-Meier estimate for government survival data
- Confidence bands for robust government estimates
- Cox PH models, constant covariates for government hazard analysis
- Cox PH models, time-dependent covariates for dynamic government studies
Graphical Procedures for Government
- High-level plotting commands
- The plot() function for government data visualization
- Displaying multivariate data in a public sector context
- Display graphics for clear government reports
- Arguments to high-level plotting functions for customizable government charts
- Basic visualisation graphs for government insights
- Multivariate relations with lattice and ggplot package for comprehensive government data representation
- Using graphics parameters for consistent government reports
- Graphics parameters list for standardized government visualizations
Automated and Interactive Reporting for Government
- Combining output from R with text for government documents
Creating HTML, PDF Documents for Government
21 Hours
Testimonials (6)
At the end of the class, we had a great overview of the language, we were provided tools to continue learning and were provided suggestions on how to continue learning. We covered AI/ML information.
Victor Prado - Global Knowledge Network Training Ltd
Course - R
The R-programming overview training is quite intensive but Tomasz is always helpful, energetic and up to date. On top of it, he is passionate about R. I would highly recommend his R sessions to anyone interested in R.
Luiza Panoschi - Global Knowledge Network Training Ltd
Course - R
Practice exercises were relevant and very helpful to reinforce the knowledge.
Andy Kwan - Environment and Climate Change Canada
Course - R
Follow-along exercises after slide presentation kept engagement.
Robin White - Environment and Climate Change Canada
Course - R
Michael was very knowledgeable and clear in his instruction of the training. Course was well structured to teach the desired subject as well as the right amount of room was left to adjust to fit our needs better. Over all, I am very happy with the course.
Brock Batey - Environment and Climate Change Canada
Course - R
I really enjoyed the knowledge of the trainer.
