In a previous post I implemented the Pearson Correlation Coefficient, a measure of how much one variable depends on another. The three sets of bivariate data I used for testing and demonstration are shown again below, along with their corresponding scatterplots. As you can see these scatterplots now have lines of best fit added, their gradients and heights being calculated using least-squares regression which is the subject of this article.
Prime numbers have been understood at least since the Ancient Greeks, and possibly since the Ancient Egyptians. In modern times their study has intensified greatly due to their usefulness, notably in encryption, and because computers enable them to be calculated to a massively higher level than could be done by hand.
The best know (and according to Wikipedia still the most widely used) method for identifying them is the Sieve of Eratosthenes, which I will implement here in C.Continue reading
Correlation is the process of quantifying the relationship between two sets of values, and in this post I will be writing code in C to calculate possibly the best-known type of correlation - the Pearson Correlation Coefficient.Continue reading
I am sticking my neck out here by implementing the notorious Bubble Sort in C. There are many sorting algorithms and even more variations on a theme, but the bubble sort is probably the best known. It’s simple to understand and the process can be illustrated with some cute animations and even Hungarian folk dancing!
You can calculate the Fibonacci Sequence by starting with 0 and 1 and adding the previous two numbers, but Binet’s Formula can be used to calculate directly any term of the sequence. This short project is an implementation of the formula in C.
This is a simple little C project demonstrating a useful application of logarithms, with the bonus of a few lines demonstrating localization.