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Course Outline
Day 1
Introduction and Preliminaries for Government
- Making R more user-friendly, including available GUIs for government use
- Rstudio for enhanced functionality
- Related software and documentation for government applications
- R in the context of statistical analysis for government
- Using R interactively for government tasks
- An introductory session for government users
- Getting help with functions and features for government operations
- R commands, case sensitivity, etc., tailored for government workflows
- Recall and correction of previous commands for efficient government use
- Executing commands from or diverting output to a file for government records
- Data permanency and removing objects for government data management
Simple Manipulations; Numbers and Vectors
- Vectors and assignment in the context of government data
- Vector arithmetic for government applications
- Generating regular sequences for government datasets
- Logical vectors for government decision-making
- Handling missing values in government data
- Character vectors for government text data
- Index vectors; selecting and modifying subsets of a data set for government analysis
- Other types of objects relevant to government operations
Objects, Their Modes and Attributes
- Intrinsic attributes: mode and length for government data management
- Changing the length of an object for government use
- Getting and setting attributes for government datasets
- The class of an object in government applications
Ordered and Unordered Factors
- A specific example for government data
- The function tapply() and ragged arrays for government analysis
- Ordered factors for government datasets
Arrays and Matrices
- Arrays in the context of government data
- Array indexing. Subsections of an array for government use
- Index matrices for government data manipulation
- The array() function
- Mixed vector and array arithmetic. The recycling rule for government operations
- The outer product of two arrays for government applications
- Generalized transpose of an array for government data transformation
- Matrix facilities
- Matrix multiplication for government calculations
- Linear equations and inversion for government problem-solving
- Eigenvalues and eigenvectors for government analysis
- Singular value decomposition and determinants for government data processing
- Least squares fitting and the QR decomposition for government statistical methods
- Forming partitioned matrices, cbind() and rbind() for government datasets
- The concatenation function, (), with arrays for government data management
- Frequency tables from factors for government reporting
Day 2
Lists and Data Frames
- Lists for government data organization
- Constructing and modifying lists
- Concatenating lists for government datasets
- Data frames
- Making data frames for government use
- attach() and detach() functions for government workflows
- Working with data frames for government analysis
- Attaching arbitrary lists for government data integration
- Managing the search path for government operations
Data Manipulation
- Selecting, subsetting observations and variables for government datasets
- Filtering, grouping for government data analysis
- Recoding, transformations for government data preparation
- Aggregation, combining data sets for government reporting
- Character manipulation, stringr package for government text processing
Reading Data
- Txt files for government data import
- CSV files for government data handling
- XLS, XLSX files for government spreadsheet integration
- SPSS, SAS, Stata, and other formats for government data compatibility
- Exporting data to txt, csv, and other formats for government data sharing
- Accessing data from databases using SQL language for government data retrieval
Probability Distributions
- R as a set of statistical tables for government use
- Examining the distribution of a set of data for government analysis
- One- and two-sample tests for government hypothesis testing
Grouping, Loops, and Conditional Execution
- Grouped expressions for government data processing
- Control statements
- Conditional execution: if statements for government decision-making
- Repetitive execution: for loops, repeat, and while for government automation
Day 3
Writing Your Own Functions
- Simple examples for government use
- Defining new binary operators for government applications
- Named arguments and defaults for government function customization
- The '...' argument for flexible government functions
- Assignments within functions for government data manipulation
- More advanced examples
- Efficiency factors in block designs for government studies
- Dropping all names in a printed array for government reports
- Recursive numerical integration for government calculations
- Scope for government function management
- Customizing the environment for government users
- Classes, generic functions, and object orientation for government data structures
Statistical Analysis in R
- Linear regression models for government studies
- Generic functions for extracting model information for government analysis
- Updating fitted models for government data refinement
- Generalized linear models
- Families for government statistical methods
- The glm() function for government regression analysis
- Classification
- Logistic Regression for government classification tasks
- Linear Discriminant Analysis for government data categorization
- Unsupervised learning
- Principal Components Analysis for government data reduction
- Clustering Methods (k-means, hierarchical clustering, k-medoids) for government data grouping
- Survival analysis
- Survival objects in R for government studies
- Kaplan-Meier estimate for government survival rates
- Confidence bands for government statistical confidence
- Cox PH models, constant covariates for government hazard analysis
- Cox PH models, time-dependent covariates for government dynamic studies
Graphical Procedures
- High-level plotting commands
- The plot() function for government data visualization
- Displaying multivariate data for government analysis
- Display graphics for government reports
- Arguments to high-level plotting functions for government customization
- Basic visualisation graphs for government data presentation
- Multivariate relations with lattice and ggplot package for government data exploration
- Using graphics parameters for government plot adjustments
- Graphics parameters list for government plotting standards
Automated and Interactive Reporting
- Combining output from R with text for government documents
- Creating html, pdf documents for government reporting
Requirements
A solid understanding of statistics for government is essential.
21 Hours
Testimonials (3)
That Haytham started with the basics and gave us enough time to do the examples and ensure that we were at the same page before we moved on to the next topic.
Jaco Dreyer - Africa Health Research Institute
Course - R Fundamentals
I enjoyed that it was very hands-on, so we were constantly having the chance to try things on, rather than just sitting listening to a lecture (for example). I felt like I am now able to go away and start using R, which I haven't been able to do before
Kathy Baisley - Africa Health Research Institute
Course - R Fundamentals
Day 1 and Day 2 were really straight forward for me and really enjoyed that experience.
