How to generate Gaussian samples

<h1>How does the Box-Muller transform work?</h1> For this project, my goal is to generate Gaussian samples in two dimensions i.e. generating samples whose x and y coordinates are independent standard normals (Gaussian with zero mean and standard deviation of 1). In <a href="https://medium.com/mti-technology/how-to-generate-gaussian-samples-347c391b7959?sk=46282403d3478247812038bfa0d1febf" rel="noopener">part 1</a>, I used the inverse Gaussian CDF to generate separately the x and y coordinates from their respective uniform samples (U₁ and U₂): <img alt="" src="https://miro.medium.com/v2/resize:fit:609/1*pUyVgBkrKOOEZoKjRsDVRg.png" style="height:119px; width:609px" /> Generate x and y coordinates from uniform samples (U₁ and U₂) using inverse transform sampling For the Box-Muller transform, I will also start with the same two uniform samples. However, I will transform these uniform samples into the x and y coordinates using much simpler formulas: <a href="https://medium.com/mti-technology/how-to-generate-gaussian-samples-3951f2203ab0">Website</a>