
Learn the basics of R programming for beginners, including installing free open-source statistical packages. Explore data visualization, statistics, simulation, and clustering techniques.
Learn how to install R programming and set up the development environment, explore the console, create projects with working directories, manage packages, and understand workspace concepts for data analysis.
Learn the basics of R programming, from console and script use to arithmetic and output. Explore core data structures (vectors, matrices, data frames, lists), variables, assignment, c(), and workspace management.
Learn to create a pie chart for a single variable from a dataset, customize colors and order, adjust the start angle and clockwise distribution, and include legends for clarity.
Explore data frames in R for beginners, creating frames with unique column names and consistent row counts, using numeric, factor, and character types, and summarizing salary and start date data.
Create a multiple line chart in R using numeric attributes from orange trees, set x and y ranges, plot the data, and customize with colors, line types, and a legend.
Explore scatter plots to visualize associations between two variables, using speed and stopping distance, and learn to add linear regression lines and variations with an R package.
Learn to create clustered bar charts in R to compare means across multiple variables using cluster analysis, with side-by-side bars and legend customization.
Learn to create scatter plots by groups, using two categorical predictors and a single quantitative outcome, with group-specific regression lines and iris species examples.
Compare means between two groups and within paired observations using two-sample and paired t-tests, load the sleep data, check distribution with histograms, and interpret p-values.
The importance of data is undeniable with companies fighting over the right to your data. The power of data has exceptionally grown in today’s world where data offers everything you need to know about a person or a potential future trend.
This has companies scouring to find amazing data analysts that can help them make sense of the large sets of data available. Companies are using this data to make decisions that can change the direction of the world.
This is why R is currently one of the most important languages on the tech market. So, if you want to master R – you’ve come to the right place!
Our R course is taking you back to the basics to help you breakdown the dynamic and easy R programming language. In this course, we will cover the fundamentals you need to learn R programming language, including the syntax, rules, how to write in R, the benefits of R programming language, how to work with large data sets and so much more!
The course has been designed for newbies as well as intermediate programmers who want to go back to the basics and want to refresh their knowledge regarding the core concepts of R Programming Language.
The course will cover in-depth topics such as getting started with R, the look and feel of R, installing R, downloading and working with variables and packages, working with data sets, creating charts and statistics, working with data including how to analyze the data, charts and statistics for association.
The course doesn’t simply focus on the theory, but also on how to actually work with data by showing you the step-by-step process and helping you build your own experimental programs. These will also help you get some insight into how you can actually write programs using R and how you can analyze data sets to create graphical representations of the data that you have.
At the end of this course, you’ll have the knowledge as well as the confidence to start working on analyzing large data sets and turning them into data that makes sense.
Enroll now and become a master analyst with this basics course!