Bøger af Sam Chen

The book is based on the materials of a training program giving by mymathcounts.com in May 2013. The book is useful for Algebra I and II school exams, Algebra I and II competitions, and SAT II Subject Math test. The topics and contents follow the curriculum of Algebra I and II from the Common Core State Standards. Please visit our web page http: //www.mymathcounts.com/index.php for pdf files of our Mathcounts and AMC books.

This is a solution book for 1990 - 2000 Mathcounts National Competition Sprint and Target round problems. Jane Chen is the author of the book "The Most Challenging MATHCOUNTS(R) Problems Solved"- 2001-2010 National Mathcounts Solutions" officially published by Mathcounts.org. For 1990-2000 Mathcounts National Team Round solutions: https: //www.amazon.com/dp/1543272304 2000-2010 Mathcounts National Team Round solutions: https: //www.amazon.com/dp/1544764421

The books (Volumes 1 to 5) can be used by 5th to 8th grade students preparing for Mathcounts State and National Competitions. Each chapter consists of (1) basic skill and knowledge section with plenty of examples, (2) exercise problems, and (3) detailed solutions to all problems. Training class is offered: http: //www.mymathcounts.com/Copied-2015-Mathcounts-State-Competition-Online-Training-program.php

Each lecture includes (1) Basic skills with examples, and (2) Exercises with answer keys. Solutions to all practice problems can be found here: http: //www.amazon.com/Lectures-Mathcounts-Competitions-Solution-Manual/dp/1530806534 Training class is offered: http: //www.mymathcounts.com/Copied-2014-Summer-Mathcounts-Training-Program.php

This book can be used by 5th to 8th grade students preparing for Mathcounts Chapter and State Competitions. School round practice tests: https: //www.amazon.com/Mathcounts-School-Competition-Practice-Yongcheng/dp/153725703X

These lectures are based on the MATHCOUNTS Curriculum. Each lecture includes (1) Basic skills with examples, and (2) Practice problems with answer keys. All the solutions for the practice problems can be found in the solution manual: http: //www.amazon.com/Lectures-Mathcounts-Competitions-Solution-Manual/dp/1530805708 Training class is offered: http: //www.mymathcounts.com/Copied-2014-Summer-Mathcounts-Training-Program.php

The books (Volumes 1 to 5) can be used by 5th to 8th grade students preparing for Mathcounts State and National Competitions. Each chapter consists of (1) basic skill and knowledge section with plenty of examples, (2) exercise problems, and (3) detailed solutions to all problems. Training class is offered: http: //www.mymathcounts.com/Copied-2015-Mathcounts-State-Competition-Online-Training-program.php

The book contains seven lectures based on the ARML contest curriculum. Each lecture includes (1) basic skills with examples, (2) practice problems, and (3) detailed solutions for each problem.

While the books in this series are primarily designed for AMC competitors, they contain the most essential and indispensable concepts used throughout middle and high school mathematics. Some featured topics include key concepts such as equations, polynomials, exponential and logarithmic functions in Algebra, various synthetic and analytic methods used in Geometry, and important facts in Number Theory. The topics are grouped in lessons focusing on fundamental concepts. Each lesson starts with a few solved examples followed by a problem set meant to illustrate the content presented. At the end, the solutions to the problems are discussed with many containing multiple methods of approach. I recommend these books to not only contest participants, but also to young, aspiring mathletes in middle school who wish to consolidate their mathematical knowledge. I have personally used a few of the books in this collection to prepare some of my students for the AMC contests or to form a foundation for others. By Dr. Titu Andreescu US IMO Team Leader (1995 - 2002) Director, MAA American Mathematics Competitions (1998 - 2003) Director, Mathematical Olympiad Summer Program (1995 - 2002) Coach of the US IMO Team (1993 - 2006) Member of the IMO Advisory Board (2002 - 2006) Chair of the USAMO Committee (1996 - 2004) I love this book! I love the style, the selection of topics and the choice of problems to illustrate the ideas discussed. The topics are typical contest problem topics: divisors, absolute value, radical expressions, Veita's Theorem, squares, divisibility, lots of geometry, and some trigonometry. And the problems are delicious. Although the book is intended for high school students aiming to do well in national and state math contests like the American Mathematics Competitions, the problems are accessible to very strong middle school students. The book is well-suited for the teacher-coach interested in sets of problems on a given topic. Each section begins with several substantial solved examples followed by a varied list of problems ranging from easily accessible to very challenging. Solutions are provided for all the problems. In many cases, several solutions are provided. By Professor Harold Reiter Chair of MATHCOUNTS Question Writing Committee. Chair of SAT II Mathematics committee of the Educational Testing Service Chair of the AMC 12 Committee (and AMC 10) 1993 to 2000.

These lectures are based on the MATHCOUNTS Curriculum. Each lecture includes (1) Basic skills with examples, and (2) Exercises with answer keys. Solutions to all practice problems can be found here: http: //www.amazon.com/Lectures-Mathcounts-Competitions-Solution-Manual/dp/1490973346 Training class is offered: http: //www.mymathcounts.com/Copied-2014-Summer-Mathcounts-Training-Program.php

This book contains the detailed solutions (not problems) to 1990- 2000 Mathcounts State Competition Sprint and Target rounds problems. Many problems are given two or more solutions. The problems are not included in this book because of the copyright issue.

The books (Volumes 1 to 5) can be used by 5th to 8th grade students preparing for Mathcounts State and National Competitions. Each chapter consists of (1) basic skill and knowledge section with plenty of examples, (2) exercise problems, and (3) detailed solutions to all problems. Training class is offered: http: //www.mymathcounts.com/Copied-2015-Mathcounts-State-Competition-Online-Training-program.php

An essential introduction to data analytics and Machine Learning techniques in the business sectorIn Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs--especially of key results--and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves.The book begins with a brief introduction to basic sampling theory and the fundamentals of simulation techniques, followed by a comparison between R and Python. It then discusses statistical diagnosis for financial security data and introduces some common tools in financial forensics such as Benford's Law, Zipf's Law, and anomaly detection. The statistical estimation and Expectation-Maximization (EM) & Majorization-Minimization (MM) algorithms are also covered. The book next focuses on univariate and multivariate dynamic volatility and correlation forecasting, and emphasis is placed on the celebrated Kelly's formula, followed by a brief introduction to quantitative risk management and dependence modelling for extremal events. A practical topic on numerical finance for traditional option pricing and Greek computations immediately follows as well as other important topics in financial data-driven aspects, such as Principal Component Analysis (PCA) and recommender systems with their applications, as well as advanced regression learners such as kernel regression and logistic regression, with discussions on model assessment methods such as simple Receiver Operating Characteristic (ROC) curves and Area Under Curve (AUC) for typical classification problems.The book then moves on to other commonly used machine learning tools like linear classifiers such as perceptrons and their generalization, the multilayered counterpart (MLP), Support Vector Machines (SVM), as well as Classification and Regression Trees (CART) and Random Forests. Subsequent chapters focus on linear Bayesian learning, including well-received credibility theory in actuarial science and functional kernel regression, and non-linear Bayesian learning, such as the Naïve Bayes classifier and the Comonotone-Independence Bayesian Classifier (CIBer) recently independently developed by the authors and used successfully in InsurTech.After an in-depth discussion on cluster analyses such as K-means clustering and its inversion, the K-nearest neighbor (KNN) method, the book concludes by introducing some useful deep neural networks for FinTech, like the potential use of the Long-Short Term Memory model (LSTM) for stock price prediction.This book can help readers become well-equipped with the following skills:* To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisions* To apply effective data dimension reduction tools to enhance supervised learning* To describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purposeThe book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries' Actuarial Statistics Exam.Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.