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Course Outline
Foundations and Initial Setup
- Making R user-friendly: Introduction to R and available GUIs
- Overview of RStudio
- Complementary software and documentation resources
- The relationship between R and statistics
- Interactive usage of R
- Guided introductory session
- Obtaining help for functions and features
- R command syntax, case sensitivity, and conventions
- Recalling and correcting previous commands
- Executing commands from files or redirecting output
- Managing data persistence and removing objects
Basic Operations: Numbers and Vectors
- Understanding vectors and assignment operators
- Performing vector arithmetic
- Creating regular sequences
- Working with logical vectors
- Handling missing values
- Manipulating character vectors
- Using index vectors to select and modify data subsets
- Exploring other object types
Objects: Modes and Attributes
- Intrinsic attributes: mode and length
- Modifying the length of an object
- Retrieving and setting attributes
- Understanding object classes
Arrays and Matrices
- Working with arrays
- Array indexing and accessing subsections
- Using index matrices
- The array() function
- Calculating the outer product of two arrays
- Generalized array transposition
- Matrix capabilities:
- Matrix multiplication
- Solving linear equations and matrix inversion
- Computing eigenvalues and eigenvectors
- Singular value decomposition and determinants
- Least squares fitting and QR decomposition
- Creating partitioned matrices using cbind() and rbind()
- Concatenating arrays
- Generating frequency tables from factors
Lists and Data Frames
- Introduction to lists
- Constructing and modifying lists:
- Concatenating lists
- Working with data frames:
- Creating data frames
- Using attach() and detach()
- Operating on data frames
- Attaching arbitrary lists
- Managing the search path
Data Manipulation Techniques
- Selecting and subsetting observations and variables
- Filtering and grouping data
- Recoding variables and applying transformations
- Aggregating data and merging datasets
- String manipulation using the stringr package
Importing and Exporting Data
- Reading text files
- Importing CSV files
- Working with XLS and XLSX files
- Loading data from SPSS, SAS, Stata, and other formats
- Exporting data to txt, CSV, and other formats
- Querying databases using SQL
Probability Distributions
- Leveraging R as a repository of statistical tables
- Analyzing the distribution of data sets
- Conducting one- and two-sample tests
Control Structures: Grouping, Loops, and Conditionals
- Grouped expressions
- Control statements:
- Conditional execution: if statements
- Repetitive execution: for loops, repeat, and while
Creating Custom Functions
- Simple function examples
- Defining new binary operators
- Named arguments and default values
- The '....' argument (ellipsis)
- Performing assignments within functions
- Advanced function examples:
- Efficiency factors in block designs
- Removing names from printed arrays
- Recursive numerical integration
- Understanding scope
- Customizing the R environment
- Classes, generic functions, and object-oriented programming
Graphical Procedures and Visualization
- High-level plotting commands:
- The plot() function
- Visualizing multivariate data
- Displaying graphics
- Configuring arguments for high-level plotting functions
- Creating basic visualization graphs
- Analyzing multivariate relationships using lattice and ggplot packages
- Utilizing graphics parameters
- Overview of the graphics parameters list
Time Series Forecasting Methods
- Seasonal adjustment techniques
- Moving average methods
- Exponential smoothing
- Extrapolation strategies
- Linear prediction models
- Trend estimation
- Assessing stationarity and ARIMA modeling
Econometric Methods (Causal Analysis)
- Introduction to regression analysis
- Multiple linear regression
- Multiple non-linear regression
- Validating regression models
- Generating forecasts from regression models
21 Hours
Testimonials (2)
Good detail on what R is used for and how to start using it right away
Hoss Shenassa - Trimac Management Services LP
Course - Introduction to R with Time Series Analysis
the matter was well presented and in an orderly manner.
