R Programming Tutorial

Learn how to create a contingency table and perform chi-square tests in R using the chisq.test() function. Discover practical applications and interpret results with confidence.

Learn about QR decomposition, the matrix factorization technique that decomposes matrix A into the product of an orthogonal matrix Q and an upper triangular matrix R.

We set na.rm = TRUE in common R functions to exclude missing (NA) values. This helps us compute accurate statistics and enhances the reliability of our results.

The non-numeric argument to binary operator error in R happens when you try to do arithmetic on non-numeric data, like a character string or factor.

Read our comprehensive guide on how to work with data structures in R programming: vectors, lists, arrays, matrices, factors, and data frames.

Learn three methods to transpose a matrix in R in this quick tutorial

How to sort a data frame in R.

Learn how to create a scatterplot in R. The basic function is plot(x, y), where x and y are numeric vectors denoting the (x,y) points to plot.

Learn how to use arithmetic and logical operators in R. These binary operators work on vectors, matrices, and scalars.

Merging data is a common task in data analysis, especially when working with large datasets. The merge function in R is a powerful tool that allows you to combine two or more datasets based on shared variables.

Improve your graphs in R with titles, text annotations, labelling of points, minor tick marks, reference lines, custom axes, and a chart legend.

Learn how to combining multiple plots in R into one graph with either the par() or layout() functions. This page includes coding examples.