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Course Outline
Introduction and preliminaries
- Enhancing user friendliness: R and available GUIs
- Understanding RStudio
- Complementary software and documentation resources
- The relationship between R and statistics
- Interactive use of R
- Conducting an introductory session
- Obtaining help for functions and features
- R command syntax, case sensitivity, and conventions
- Recalling and correcting previous commands
- Executing commands from files and directing output
- Managing data persistence and removing objects
Simple manipulations; numbers and vectors
- Understanding vectors and assignment
- Vector arithmetic operations
- Generating regular sequences
- Working with logical vectors
- Handling missing values
- Working with character vectors
- Using index vectors to select and modify data subsets
- Exploring other object types
Objects, their modes and attributes
- Intrinsic attributes: mode and length
- Modifying the length of an object
- Retrieving and setting attributes
- Determining the class of an object
Arrays and matrices
- Working with arrays
- Array indexing and accessing subsections
- Utilizing index matrices
- The array() function
- Computing the outer product of two arrays
- Generalized transpose operations for arrays
- Matrix capabilities
- Matrix multiplication
- Solving linear equations and inversion
- Calculating eigenvalues and eigenvectors
- Singular value decomposition and determinants
- Least squares fitting and QR decomposition
- Creating partitioned matrices using cbind() and rbind()
- Concatenating arrays with the c() function
- Generating frequency tables from factors
Lists and data frames
- Understanding lists
- Constructing and modifying lists
- Concatenating lists
- Working with data frames
- Creating data frames
- Using attach() and detach()
- Manipulating data frames
- Attaching arbitrary lists
- Managing the search path
Data manipulation
- Selecting, subsetting observations and variables
- Filtering and grouping data
- Recoding and transforming data
- Aggregating and merging data sets
- String manipulation using the stringr package
Reading data
- Importing text files
- Importing CSV files
- Importing XLS and XLSX files
- Importing data from SPSS, SAS, Stata, and other formats
- Exporting data to TXT, CSV, and other formats
- Accessing database content via SQL language
Probability distributions
- Utilizing R as a repository for statistical tables
- Examining data distribution patterns
- Conducting one- and two-sample tests
Grouping, loops and conditional execution
- Using grouped expressions
- Implementing control statements
- Conditional execution with if statements
- Repetitive execution using for loops, repeat, and while
Writing your own functions
- Exploring simple examples
- Defining new binary operators
- Using named arguments and default values
- Understanding the '...' argument
- Performing assignments within functions
- Reviewing more advanced examples
- Efficiency factors in block designs
- Removing all names from a printed array
- Implementing recursive numerical integration
- Understanding scope
- Customizing the R environment
- Exploring classes, generic functions, and object orientation
Graphical procedures
- High-level plotting commands
- Using the plot() function
- Visualizing multivariate data
- Displaying graphics
- Configuring arguments for high-level plotting functions
- Creating basic visualization graphs
- Analyzing multivariate relations with lattice and ggplot packages
- Utilizing graphics parameters
- Overview of the graphics parameters list
Time series Forecasting
- Performing seasonal adjustment
- Applying moving averages
- Utilizing exponential smoothing
- Extrapolation techniques
- Implementing linear prediction
- Estimating trends
- Assessing stationarity and ARIMA modelling
Econometric methods (causal methods)
- Conducting regression analysis
- Performing multiple linear regression
- Performing 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.
