R is a major competitor to Python for statistics and data analysts. It is used in the social and economic sciences to find cause and effect relationships, compare samples, and create visual reports and graphs.
The language was developed by scientists in the Department of Statistics at the University of Auckland. At first, it was an internal tool, but then it was made available to everyone – it turned out to be very successful.
This is an important point: R is developed by statisticians for statisticians – it already has popular statistical tests, data analysis methods, and convenient graphing tools. Not all popular general-purpose languages have such capabilities.
Before learning the R language, many people start by learning Java. And while studying it, beginners may have some problems. If you get in this situation, you should get Java programming homework help. On special services, you can go through difficult sections with an expert’s help and can continue your study further.
Tips to start your R programming assignment
- Learn graphical user interfaces and interactive tools
In addition to the command line interface, there are graphical user interfaces and interactive tools for R that make doing your assignment easier and more enjoyable. They are available free of charge and are distributed under the free license of the GNU GPL. Here are the most popular ones:
- RStudio development environment. It can be installed on Windows, Linux, and MacOS. RStudio has visual highlighting of the R code, easy navigation through the program text, revision history, sorting tabular data by columns, displaying graphs in a separate window – in general, everything that should be in a normal development environment.
- Jupyter Notebook web interface. It is a notepad application for creating and sharing programs in R and many other languages that allow you to work with data. It is opened in a browser, displaying code and graphics at the same time – pictures, equations.
- The Anaconda distribution is a collection of popular libraries and programs for conveniently working with data in R. By the way, there is also a version for Python, which is conveniently installed from a single file and includes RStudio, the Jupyter Notebook web interface, and many other applications.
- Learn how to process, clean, and transform data for research
For example, let’s say you need to do an assignment where you need to find out the average number of users who downloaded the mobile app for each summer and fall month. R allows you to exclude winter and spring from the schedule and group them by month for further calculations.
- Learn how to conduct statistical tests
Let’s say you need to do an assignment where you should find out if the life expectancy of men and women is different. To do this, you can run a t-test – its results will show if there are statistically significant differences between the data.
- Learn how to perform exploratory analysis
The data must be checked for normality because many statistical methods (for example, the same t-test) require normal distribution in the sources. A normal distribution assumes that most of the data is grouped around the mean, and the rest is much smaller. Such a distribution often occurs in life: there are more people of average height in the world, and there are fewer tall and short people. R has tools for checking normality using graphs and tests, which is very helpful while doing assignments.
Keep our tips in mind before you start doing your R programming assignment. If you have a certain amount of knowledge, you can do your homework much better. Good luck!
