Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction and Basics
- Making R User-Friendly: Overview of R and Available GUIs
- Introduction to RStudio
- Complementary Software and Documentation
- Understanding the Relationship Between R and Statistics
- Interactive Use of R
- Conducting an Introductory Session
- Accessing Help for Functions and Features
- Understanding R Commands, Case Sensitivity, and Syntax
- Reviewing and Correcting Previous Commands
- Executing Commands and Redirecting Output to Files
- Managing Data Permanency and Removing Objects
Basic Manipulations: Numbers and Vectors
- Understanding Vectors and Assignment
- Performing Vector Arithmetic
- Generating Regular Sequences
- Working with Logical Vectors
- Handling Missing Values
- Utilizing Character Vectors
- Using Index Vectors to Select and Modify Data Subsets
- Exploring Other Data Object Types
Objects, Modes, and Attributes
- Understanding Intrinsic Attributes: Mode and Length
- Modifying Object Lengths
- Retrieving and Setting Attributes
- Determining the Class of an Object
Arrays and Matrices
- Working with Arrays
- Array Indexing and Subsections
- Utilizing Index Matrices
- The array() Function
- Calculating the Outer Product of Two Arrays
- Performing Generalized Transposition of 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()
- Concatenation Functions with Arrays
- 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 Techniques
- Selecting and Subsetting Observations and Variables
- Filtering and Grouping Data
- Recoding and Transforming Data
- Aggregation and Combining Data Sets
- String Manipulation Using the stringr Package
Importing Data
- Reading TXT Files
- Reading CSV Files
- Reading XLS and XLSX Files
- Importing Data from SPSS, SAS, Stata, and Other Formats
- Exporting Data to TXT, CSV, and Other Formats
- Accessing Database Data Using SQL
Probability Distributions
- Using R as a Statistical Reference Table
- Analyzing Data Distributions
- Conducting One- and Two-Sample Tests
Grouping, Loops, and Conditional Logic
- Working with Grouped Expressions
- Control Statements
- Conditional Execution: Using if Statements
- Repetitive Execution: for Loops, repeat, and while
Creating Custom Functions
- Basic Examples of Function Creation
- Defining New Binary Operators
- Utilizing Named Arguments and Default Values
- Understanding the '...' Argument
- Performing Assignments Within Functions
- Advanced Examples
- Efficiency Factors in Block Designs
- Removing Names from Printed Arrays
- Recursive Numerical Integration
- Understanding Scope
- Customizing the Environment
- Working with Classes, Generic Functions, and Object Orientation
Graphical Procedures
- High-Level Plotting Commands
- The plot() Function
- Visualizing Multivariate Data
- Creating Display Graphics
- Configuring Arguments for High-Level Plotting Functions
- Creating Basic Visualization Graphs
- Analyzing Multivariate Relationships with the lattice and ggplot Packages
- Utilizing Graphics Parameters
- Overview of Graphics Parameters List
Time Series Forecasting
- Performing Seasonal Adjustment
- Applying Moving Averages
- Implementing Exponential Smoothing
- Performing Extrapolation
- Conducting Linear Prediction
- Estimating Trends
- Ensuring Stationarity and ARIMA Modeling
Econometric Methods (Causal Analysis)
- Conducting Regression Analysis
- Implementing Multiple Linear Regression
- Implementing 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.
