Studieren Sie Sportwissenschaft, sehen Sie Ihren Fokus in erster Linie in der praktischen Anwendung Ihres Wissens und sind wahrscheinlich überrascht, dass Sie sich in Ihrem Studium oder in einer weiteren Qualifikation nun erneut mit Mathematik und Statistik auseinandersetzen müssen.
The basic stochastic approximation algorithms introduced by Robbins and MonroandbyKieferandWolfowitzintheearly1950shavebeenthesubject of an enormous literature, both theoretical and applied.
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field.
Advances in Growth Curve Models: Topics from the Indian Statistical Institute is developed from the Indian Statistical Institute's A National Conference on Growth Curve Models.
This textbook provides an accessible overview of statistical learning methods and techniques, and includes case studies using the statistical software Stata.
Missing Data Analysis in Practice provides practical methods for analyzing missing data along with the heuristic reasoning for understanding the theoretical underpinnings.
The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.
Developing a model-based approach that enables any cross-over trial, of any degree of imbalance, to be analyzed both for direct effects and for residual effects, using consistent procedures that employ commercially available statistical software, this text offers a guide to the analysis of cross-over designs.
Dieses Lehrbuch bietet eine leicht verständliche Einführung in die moderne Finanzmathematik und erläutert grundlegende mathematische Konzepte der Optionsbewertung, der Portfolio-Optimierung und des Risikomanagements.
Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations.
The fields of Artificial Intelligence (AI) and Machine Learning (ML) have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications.
This festschrift includes papers authored by many collaborators, colleagues, and students of Professor Thomas P Hettmansperger, who worked in research in nonparametric statistics, rank statistics, robustness, and mixture models during a career that spanned nearly 40 years.
This book is intended to make recent results on the derivation of higher order numerical schemes for random ordinary differential equations (RODEs) available to a broader readership, and to familiarize readers with RODEs themselves as well as the closely associated theory of random dynamical systems.
This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty.
This book explores the reliability of official statisticaldata in the ASEAN (the Association of Southeast Asian Nations), and thebenefits of a better vocabulary to discuss the quality of publicly availabledata to address the needs of all users.
This book is devoted to the study of multivariate discrete q-distributions, which is greatly facilitated by existing multivariate q-sequences and q-functions.
Im Fokus dieses Buches steht die quantitative Modellierung und statistische Messung von Ereignisrisiken: Es werden statistische Schätzverfahren zur Quantifizierung von Ereignisrisiken und statistische Testverfahren zum Einsatz im Rahmen der Risikokontrolle präsentiert.
Agreement assessment techniques are widely used in examining the acceptability of a new or generic process, methodology and/or formulation in areas of lab performance, instrument/assay validation or method comparisons, statistical process control, goodness-of-fit, and individual bioequivalence.
With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples.
This book is about using interactive and dynamic plots on a computer screen as part of data exploration and modeling, both alone and as a partner with static graphics and non-graphical computational methods.
The normal or bell curve distribution is far more common in statistics textbooks than it is in real factories, where processes follow non-normal and often highly skewed distributions.
