# VARIANCE

This book is a a discussion of the calculation of specific formulas in finance. The field of finance has seen a rapid development in recent years, with increasing mathematical sophistication. While the formalization of the field can be traced back to the work of Markowitz (1952) on investors mean-variance decisions and Modigliani and Miller (1958) ...

This book is a must-have for anyone serious about rendering in real time. With the announcement of new ray tracing APIs and hardware to support them, developers can easily create real-time applications with ray tracing as a core component. As ray tracing on the GPU becomes faster, it will play a more central role in real-time rendering. Ray Tracing...

This book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear,...

AI is transforming numerous industries. Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects. This book is focused not on teaching you ML algorithms, but on how to make ML algorithms work. After reading Machine Learning Yearning, you will be able to: - Prioritize the most promising direc...

This book analyses the domestic politics of African dominant party regimes, most notably African governments' survival strategies, to explain their variance of opinions and responses towards the reforming policies of the EU. The author discredits the widespread assumption that the growing presence of China in Africa has made the EU's task...

This book focuses on the linear selection index (LSI) theory and its statistical properties. It addresses the single-stage LSI theory by assuming that economic weights are fixed and known - or fixed, but unknown - to predict the net genetic merit in the phenotypic, marker and genomic context. Further, it shows how to combine the LSI theory with the...

Drawing on new research material from ten European countries, Asylum Determination in Europe: Ethnographic Perspectives brings together a range of detailed accounts of the legal and bureaucratic processes by which asylum claims are decided.The book includes a legal overview of European asylum determination procedures, followed by sections on the di...

This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III pr...

This open access thematic report identifies factors and conditions that can help schools and education systems promote tolerance in a globalized world. The IEA's International Civic and Citizenship Study (ICCS) is a comparative research program designed to investigate the ways in which young people are prepared to undertake their roles as citi...

This book focuses on the concepts, tools and techniques needed to successfully model ever-changing time-series data. It emphasizes the need for general models to account for the complexities of the modern world and how these can be applied to a range of issues facing Earth, from modelling volcanic eruptions, carbon dioxide emissions and global temp...

This volume offers insights from modelling measures of parental involvement and their relationship with student reading literacy across countries, exploring and incorporating cultural differences. This is a significant contribution to a field where cross-cultural comparisons from a triangulated perspective are sparse. For readers interested in expl...

If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, ...

This book is a practical introduction to multilevel modelling or multilevel analysis (MLA) – a statistical technique being increasingly used in public health and health services research. The authors begin with a compelling argument for the importance of researchers in these fields having an understanding of MLA to be able to judge not only the g...

For medical and health workers this book is a must-have, because statistical methods in these fields are vital, and no equivalent work is available. For medical and health students this is equally true.A unique point is its low threshold, textually simple and at the same time full of self-assessment opportunities. Other unique points are the succin...

This free book will focus on theoretical aspects of Statistical Learning and Sequential Prediction. Until recently, these two subjects have been treated separately within the learning community. The course will follow a unified approach to analyzing learning in both scenarios. To make this happen, we shall bring together ideas from probability and ...

This book is directed toward students for whom mathematical statistics is or will become an important part of their lives. Obviously, such students should be able to work through the details of 'hard' proofs and derivations. In addition, students at this level should acquire, or begin acquiring, a deep appreciation for the field, includin...

This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters...

This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. ...

This book offers an easily accessible and comprehensive guide to the entire market research process, from asking market research questions to collecting and analyzing data by means of quantitative methods. It is intended for all readers who wish to know more about the market research process, data management, and the most commonly used methods in m...

The revised 2nd edition of this book provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribut...

This book is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.With careful treatment of topics that fill the curricular needs for the course, Probab...

Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, w...

As machine learning is increasingly leveraged to find patterns, conduct analysis, and make decisions - sometimes without final input from humans who may be impacted by these findings - it is crucial to invest in bringing more stakeholders into the fold. This book of Python projects in machine learning tries to do just that: to equip the developers ...

Ccurrently many of Julia's users are hard-core developers that contribute to the language's standard libraries, and to the extensive package eco-system that surrounds it. Therefore, much of the Julia material available at present is aimed at other developers rather than end users. This is where our book comes in, as it has been written wi...

The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The student should have a basic understanding of statistical inference such as contained in "Statistical inference for data science". The book gives a rigorous treatment of the elementary concepts of regr...

The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The book gives a rigorous treatment of the elementary concepts in statistical inference from a classical frequentist perspective. After reading this book and performing the exercises, the student will understand th...

Statistics is quickly becoming the most important and multi-disciplinary field of mathematics. According to the American Statistical Association, statistician is one of the top ten fastest-growing occupations and statistics is one of the fastest-growing bachelor degrees. Statistical literacy is essential to our data driven society. Despite the ...

Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite po...

The purpose of the 3rd edition of this book is to give a sound and self-contained (in the sense that the necessary probability theory is included) introduction to classical or mainstream statistical theory. It is not a statistical-methods-cookbook, nor a compendium of statistical theories, nor is it a mathematics book. The book is intended to be a ...

This book provides an algorithmic perspective to autonomous robotics to students with a sophomore-level of linear algebra and probability theory. Robotics is an emerging field at the intersection of mechanical engineering, electrical engineering, and computer science. With computers becoming more powerful, making robots smart is getting more and mo...