This is a template for an empirical term paper at the university. It comes with a nice folder structure that allows a good overview of the different text parts.
It includes various options that are customizable (e.g. cover page/no cover page; including/excluding table of content, list of figures/tables) and also gives a quick introduction into the very basics of LaTeX such as highlighting, citing, writing, including tables, figures, and mathematical equations.
Linear regression is one of the most widely used statistical methods available today. It is used by data analysts and students in almost every discipline. However, for the standard ordinary least squares method, there are several strong assumptions made about data that is often not true in real world data sets. This can cause numerous problems in the least squares model. One of the most common issues is a model overfitting the data. Ridge Regression and LASSO are two methods used to create a better and more accurate model. I will discuss how overfitting arises in least squares models and the reasoning for using Ridge Regression and LASSO include analysis of real world example data and compare these methods with OLS and each other to further infer the benefits and drawbacks of each method.
Visualization is a descriptive way to ensure the audience attention and to make people better understand the content of a given topic. Nowadays, in the world of science and technology, visualization has become a necessity. However, it is a huge challenge to visualize varying amounts of data in a static or dynamic form. In this paper we describe the role, value and importance of visualization in maths and science. In particular, we are going to explain in details the benefits and shortages of visualization in three main domains: Mathematics, Programming and Big Data. Moreover, we will show the future challenges of visualization and our perspective how to better approach and face with the recent problems through technical solutions.
Here we discuss the path integral formalism for quantization of fields. The basic idea is reviewed and explained. This is completely based on the book ``Quantum Field Theory A Modern Introduction" by Michio Kaku. For calculation natural system of units is taken.