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Math 471 Homework 1

Dicas para a preparação de listas de exercícios da disciplina MAC0239 (Introdução à Lógica e Verificação de Programas) no IME-USP. Tips for preparing exercises for MAC0239 (Introduction to Logic and Program Verification) at IME-USP.

Mandeep Kumar's résumé, using a template downloaded from LaTeXTemplates.com. Original author of the template: Debarghya Das With extensive modifications by: Vel License: CC BY-NC-SA 3.0

The impact crater of a small metal ball of 63.7 grams (0.0637kg) is dropped from 8 different heights, ranging from 0.20m to 0.90m was observed. A mean was measured for the craters diameter. Using the equation E=mg$\Delta$h given that we have m, and g is a constant of 9.81 we can find the kinetic energy of the ball on impact. The relationship between crater diameter, D, and impact energy, E, is given by D=kE$^n$ where K is constant and n is found by the gradient of the graph and is also constant. This can be modified to give $\log D = n\log E + \log k$.

Created using the William Resume/CV XeLaTeX Template Version 1.0 (22/1/2015) This template has been downloaded from LaTeXTemplates.com Original author: Howard Wilson with extensive modifications by Vel

A lecture on intermediate proofs that I taught at ARML.

El barómetro es un instrumento de medición atmosérica, específicamente utilizado en la determinación de la fuerza por unidad de superficie ejercida por el peso de la atmósfera. Existe un gran número de equipos atmoféricos con distintos tipos de estos aparátos y son diariamente utilizados ya que la presión atmosférica juega un papel importante en la determinación y pronóstico del tiempo así como en el área de investigación al momento de realizarse experimentos ya que pueden llegar a afectar o hacer variar el funcionamiento de muchos aparatos electrónicos y mecánicos.

IB chemistry essay

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.