R Programming for Statistics and Data Science

Instructor: Packt - Course Instructors

What you'll learn

  •   Differentiate between data structures (vectors, matrices, data frames)
  •   Conduct hypothesis testing and interpret statistical results
  •   Assess the fit of linear regression models
  •   Visualize data using ggplot2 for insightful presentation

    • Skills you'll gain

  •   Data Wrangling
  •   Statistical Modeling
  •   Descriptive Statistics
  •   Statistical Inference
  •   Statistical Analysis
  •   Programming Principles
  •   R Programming
  •   Data Visualization
  •   Ggplot2
  •   Probability & Statistics
  •   Tidyverse (R Package)
  •   Regression Analysis
  •   Data Structures
  •   Data Transformation
  •   Data Manipulation
  •   Data Analysis
  •   Exploratory Data Analysis
  •   Statistical Hypothesis Testing

    • There are 11 modules in this course

    This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This in-depth course starts by walking you through the basics of R programming, from setting up the environment with R and RStudio to understanding its user interface. As you move through the early sections, you'll dive into foundational programming concepts like data types, functions, and vector operations, enabling you to build a solid base in R. You’ll also learn how to handle complex structures like matrices and data frames, making it easy to organize and manipulate data efficiently. As the course progresses, you’ll explore more advanced R capabilities, such as creating and modifying data frames, using the popular dplyr package, and working with relational, logical operators, and loops. The lessons on data manipulation and visualization offer hands-on experience in cleaning and presenting data, covering essential tools like ggplot2 for creating insightful graphs and charts. These skills will help you analyze data and make data-driven decisions more effectively. Finally, the course delves into statistics with exploratory data analysis, hypothesis testing, and linear regression modeling. By mastering these techniques, you'll gain the ability to analyze real-world data, draw meaningful insights, and make predictions. Whether you’re an aspiring data scientist or a statistician looking to hone your skills, this course provides everything you need to succeed in the data science field using R. This course is designed for aspiring data scientists, statisticians, and professionals looking to master R for data analysis. Basic knowledge of programming is beneficial, but not required.

    The Building Blocks of R

    Vectors and Vector Operations

    Matrices

    Fundamentals of Programming with R

    Data Frames

    Manipulating Data

    Visualizing Data

    Exploratory Data Analysis

    Hypothesis Testing

    Linear Regression Analysis

    Explore more from Data Analysis

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    Data Analysis with R Programming

    R Programming

    Foundations of R Programming and Basic Data Manipulation

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