R from Scratch - An Intro to Data Analytics
Edition: 2
Copyright: 2025
Pages: 300
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$103.00 USD
R from Scratch: An Intro to Data Analytics is an online course package that teaches students how to use the R language to perform data analysis tasks. R is a powerful and versatile language that can handle various types of data, from numeric to categorical, from structured to unstructured, from small to large.
Whether an undergraduate student or an experienced data analyst, this course helps readers learn new skills and techniques to explore, visualize, and communicate your data insights using R.
R from Scratch: An Intro to Data Analytics is divided into two parts:
- Part One covers the basics of R, such as how to install and run R, how to work with data structures and objects, such as vectors, matrices, lists, and data frames, and how to write and test your R code, using functions, loops, and conditional statements.
- Part Two introduces readers to the basic concepts of data analytics, such as descriptive statistics, hypothesis testing, regression, and ANOVA, and how to use R to apply them to their data. Readers also learn how to create and customize various types of data visualizations, such as plots, charts, and maps, and how to communicate their data analysis results effectively.
Part 1 Introduction to the R Language
Chapter 1: Introduction
Chapter 2: The Absolute Basics
Chapter 3: R Data Structures
Chapter 4: Data Importing and Exporting in R
Chapter 5: Basic Data Visualization
Chapter 6: Conditional Statements and Functions
Chapter 7: Data Manipulation With dplyr
Chapter 8: Loops in R
Part 2 Data Analytics with R
Chapter 9: Data Analytics Concepts
Chapter 10: More Data Wrangling
Chapter 11: String Manipulation
Chapter 12: Time Series Analysis
Chapter 13: Advanced Data Visualization and Communication
Chapter 14: Basics of Statistical Modeling
Chapter 15: Predictive Analysis
Chapter 16: What is Next?
Dr. Jasser has a PhD in computer science from the University of Central Florida (UCF), a master’s in management of information systems from Lawrence Technological University, and a bachelor’s in computer science from the New York Institute of Technology. He started teaching Visual Basic labs in 2016 and mentored students on data analytics projects at UCF. He was an adjunct professor at Florida Polytechnic University and taught various data analytics courses like Python for Data Analytics, Cloud Infrastructure and Services, and Data Analytics for Smart City and Transportation. He is now the director of the Data Analytics minor at Rollins College and teaches courses like Fundamentals of Data Science and Analytics, Machine Learning, Social Network Analysis, and Information Systems.
R from Scratch: An Intro to Data Analytics is an online course package that teaches students how to use the R language to perform data analysis tasks. R is a powerful and versatile language that can handle various types of data, from numeric to categorical, from structured to unstructured, from small to large.
Whether an undergraduate student or an experienced data analyst, this course helps readers learn new skills and techniques to explore, visualize, and communicate your data insights using R.
R from Scratch: An Intro to Data Analytics is divided into two parts:
- Part One covers the basics of R, such as how to install and run R, how to work with data structures and objects, such as vectors, matrices, lists, and data frames, and how to write and test your R code, using functions, loops, and conditional statements.
- Part Two introduces readers to the basic concepts of data analytics, such as descriptive statistics, hypothesis testing, regression, and ANOVA, and how to use R to apply them to their data. Readers also learn how to create and customize various types of data visualizations, such as plots, charts, and maps, and how to communicate their data analysis results effectively.
Part 1 Introduction to the R Language
Chapter 1: Introduction
Chapter 2: The Absolute Basics
Chapter 3: R Data Structures
Chapter 4: Data Importing and Exporting in R
Chapter 5: Basic Data Visualization
Chapter 6: Conditional Statements and Functions
Chapter 7: Data Manipulation With dplyr
Chapter 8: Loops in R
Part 2 Data Analytics with R
Chapter 9: Data Analytics Concepts
Chapter 10: More Data Wrangling
Chapter 11: String Manipulation
Chapter 12: Time Series Analysis
Chapter 13: Advanced Data Visualization and Communication
Chapter 14: Basics of Statistical Modeling
Chapter 15: Predictive Analysis
Chapter 16: What is Next?
Dr. Jasser has a PhD in computer science from the University of Central Florida (UCF), a master’s in management of information systems from Lawrence Technological University, and a bachelor’s in computer science from the New York Institute of Technology. He started teaching Visual Basic labs in 2016 and mentored students on data analytics projects at UCF. He was an adjunct professor at Florida Polytechnic University and taught various data analytics courses like Python for Data Analytics, Cloud Infrastructure and Services, and Data Analytics for Smart City and Transportation. He is now the director of the Data Analytics minor at Rollins College and teaches courses like Fundamentals of Data Science and Analytics, Machine Learning, Social Network Analysis, and Information Systems.