Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.
You will learn how to predict a team’s won loss record from the number of runs, points, or goals scored by a team and its opponents. Then we will introduce you to multiple regression and show how multiple regression is used to evaluate baseball hitters. Excel data tables, VLOOKUP, MATCH, and INDEX functions will be discussed.
You will concentrate on learning important Excel tools including Range Names, Tables, Conditional Formatting, PivotTables, and the family of COUNTIFS, SUMIFS, and AVERAGEIFS functions. You will concentrate on learning important Excel tools including Range Names, Tables, Conditional Formatting, PivotTables, and the family of COUNTIFS, SUMIFS, and AVERAGEIFS functions.
You will learn how Monte Carlo simulation works and how it can be used to evaluate a baseball team’s offense and the famous DEFLATEGATE controversy.
You will learn how to evaluate baseball fielding, baseball pitchers, and evaluate in game baseball decision-making. The math behind WAR (Wins above Replacement) and Park Factors will also be discussed. Modern developments such as infield shifts and pitch framing will also be discussed.
You will learn basic concepts involving random variables (specifically the normal random variable, expected value, variance and standard deviation.) You will learn how regression can be used to analyze what makes NFL teams win and decode the NFL QB rating system. You will also learn that momentum and the “hot hand” is mostly a myth. Finally, you will use Excel text functions and the concept of Expected Points per play to analyze the effectiveness of a football team’s play calling.
You will learn how two-person zero sum game theory sheds light on football play selection and soccer penalty kick strategies. Our discussion of basketball begins with an analysis of NBA shooting, box score based player metrics, and the Four Factor concept which explains what makes basketball teams win.
You will learn about advanced basketball concepts such as Adjusted plus minus, ESPN’s RPM, SportVu data, and NBA in game decision-making.
You will learn how to use game results to rate sports teams and set point spreads. Simulation of the NCAA basketball tournament will aid you in filling out your 2016 bracket. Final 4 is in Houston!
You will learn how to rate NASCAR drivers and get an introduction to sports betting concepts such as the Money line, Props Bets, and evaluation of gambling betting systems.
You will learn how Kelly Growth can optimize your sports betting, how regression to the mean explains the SI cover jinx and how to optimize a daily fantasy sports lineup. We close with a discussion of golf analytics.
Final exam has 10 questions. Please download and open Excel files before taking the exam. You will be referred to Excel files during the exam. Each question is wort 1 point. You need to answer 6 questions or more correctly to pass the exam.
Learn to master differential equations and special functions in this graduate level course. In this advanced math course, you will learn how to build solutions to important differential equations in physics and their asymptotic expansions. Armed with the tools mastered in this course, you will have a solid command of the methods of tackling differential equations and integrals encountered in theoretical and applied physics and material science.
¿Por qué las grúas no se vuelcan al levantar grandes pesos? ¿por qué las mesas sólo necesitan tres patas (no alineadas) para apoyarse? Este curso te guiará paso a paso en los conocimientos básicos para entender el equilibrio de estructuras simples.
Este curso provee al estudiante con conceptos y herramientas matemáticas para modelar problemas en física, que al aplicar podrá enfrentar con éxito los cursos de física universitarios. Así pues, la filosofía de este curso consiste en cubrir temas conceptuales relativos a la Física y desarrollar tu capacidad de aprender y aplicarlos en tu vida profesional.
Discrete mathematics forms the mathematical foundation of computer and information science. It is also a fascinating subject in itself. Learners will become familiar with a broad range of mathematical objects like sets, functions, relations, graphs, that are omnipresent in computer science. Perhaps more importantly, they will reach a certain level of mathematical maturity - being able to understand formal statements and their proofs; coming up with rigorous proofs themselves; and coming up with interesting results.
This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
Enumerative combinatorics deals with finite sets and their cardinalities. In other words, a typical problem of enumerative combinatorics is to find the number of ways a certain pattern can be formed. In the first part of our course we will be dealing with elementary combinatorial objects and notions: permutations, combinations, compositions, Fibonacci and Catalan numbers etc. In the second part of the course we introduce the notion of generating functions and use it to study recurrence relations and partition numbers.
Aprenderemos a modelizar problemas del mundo real mediante su representación con grafos y a resolverlos mediante sus algoritmos asociados. Este curso trata la Teoría de Grafos desde el punto de vista de la modelización, lo que nos permitirá con posterioridad resolver muchos problemas de diversa índole. Presentaremos ejemplos de los distintos problemas en un contexto real, analizaremos la representación de éstos mediante grafos y veremos los algoritmos necesarios para resolverlos.
El curso le permitirá al estudiante apropiarse de los principios y leyes requeridos para analizar problemas de Ingeniería mediante la Estática de partículas como punto inicial para problemas de mecánica, estos conocimientos los podrá aplicar en cursos avanzados y en el análisis de sistemas de fuerzas y momentos en la vida cotidiana.
MOOCs – Massive Open Online Courses – enable students around the world to take university courses online. This guide, by the instructors of edX’s most successful MOOC in 2013-2014, Principles of Written English (based on both enrollments and rate of completion), advises current and future students how to get the most out of their online study, covering areas such as what types of courses are offered and who offers them, what resources students need, how to register, how to work effectively with other students, how to interact with professors and staff, and how to handle assignments. This second edition offers a new chapter on how to stay motivated. This book is suitable for both native and non-native speakers of English, and is applicable to MOOC classes on any subject (and indeed, for just about any type of online study).