The line of best fit via transformations
In this note, we will show how transformations can be used to obtain a radically simple derivation of the equation of the line of best fit. Our approach also gives a simple geometric interpretation of the Pearson correlation coefficient.
Notes on quadratic functions for Mathematics Standard Level
Statistics Formulae (Lind et. al. 2015)
Collection of statistics formulae taken from the perennial text book Lind, Douglas A. et. al. (2015): Statistical Techniques in Business and Economics, 16 ed. (2015).
Wolfgang W. Stoettner
Clean more like I wanna clill myself
A concise guide for anyone that's met with the terrible fate of having to program in Clean (so mainly for Radboud University students).
Melle P. Starke & Crippling D. Pression
Two Simple Proofs for Cramer's Rule
Cramer's rule is usually explained by cofactor expansion of determinant. This note explains two alternative and simple proofs.
Frank the Bunny