Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process
Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học thế giới đề tài: Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical and binary traits using Gibbs sampling
Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Bayesian analysis of mixed linear models via Gibbs sampling with an application to litter size in Iberian pigs
This book was written for graduate students and researchers in statistics and the
social sciences. Our intent in writing the book was to bridge the gap between
recent theoretical developments in statistics and the application of these methods
to ordinal data. Ordinal data are the most common form of data acquired in the
social sciences, but the analysis of such data is generally performed without regard
to their ordinal nature.
Think Bayes is an introduction to Bayesian statistics using computational methods and Python programming language. Bayesian statistics are usually presented mathematically, but many of the ideas are easier to understand computationally. Contents: Bayes's Theorem; Computational statistics; Tanks and Trains; Urns and Coins; Odds and addends; Hockey; The variability hypothesis; Hypothesis testing.
Almost all research in the social and behavioral sciences, and also in eco
nomic and marketing research, criminological research, and social medical
research deals with the analysis of categorical data. Categorical data are
quantified as either nominal or ordinal variables. This volume is a collec
tion of up-to-date studies on modern categorical data analysis methods,
emphasizing their application to relevant and interesting data sets.
A standard form of analysis for linguistic typology is the universal implication. These implications state facts about the range of extant languages, such as “if objects come after verbs, then adjectives come after nouns.” Such implications are typically discovered by painstaking hand analysis over a small sample of languages. We propose a computational model for assisting at this process. Our model is able to discover both well-known implications as well as some novel implications that deserve further study.
Speech style accommodation refers to shifts in style that are used to achieve strategic goals within interactions. Models of stylistic shift that focus on speciﬁc features are limited in terms of the contexts to which they can be applied if the goal of the analysis is to model socially motivated speech style accommodation. In this paper, we present an unsupervised Dynamic Bayesian Model that allows us to model stylistic style accommodation in a way that is agnostic to which speciﬁc speech style features will shift in a way that resembles socially motivated stylistic variation.
An MBA is a curious beast: it can accelerate your career, even if it has limited
practical value in day-to-day management.
Top employers hire top MBAs, but not because MBAs have mastered the
mysteries of management. An MBA is a hallmark of personal commitment,
effort, and ambition which employers value more than the actual content of
the MBA course.
Fisher and Mahalanobis described Statistics as the key technology of the twentieth century. Since then Statistics has evolved into a ﬁeld that has many applications in all sciences and areas of technology, as well as in most areas of decision making such as in health care, business, federal statistics and legal proceedings. Applications in statistics such as inference for Causal effects, inferences about the spatio- temporal processes, analysis of categorical and survival data sets and countless other functions play an essential role in the present day world.
Applied statistics for civil and environmental engineers has many contents: Preliminary Data Analysis, Basic Probability Concepts, Random Variables and Their Properties, Model Estimation and Testing, Methods of Regression and Multivariate Analysis, Frequency Analysis of Extreme Events, Simulation Techniques for Design, Risk and Reliability Analysis, Bayesian Decision Methods and Parameter Uncertainty.
objective or subjective, when making decisions under uncertainty. This is especially true
when the consequences of the decisions can have a significant impact, financial or
otherwise. Most of us make everyday personal decisions this way, using an intuitive process
based on our experience and subjective judgments.
Mainstream statistical analysis, however, seeks objectivity by generally restricting the
information used in an analysis to that obtained from a current set of clearly relevant data.
Null hypothesis signiﬁcance testing (NHST) is one of the main research tools in
social and behavioral research. It requires the speciﬁcation of a null hypothesis,
an alternative hypothesis, and data in order to test the null hypothesis. The
main result of a NHST is a p-value . An example of a null hypothesis and
a corresponding alternative hypothesis for a one-way analysis of variance is:
This chapter deals with independent component analysis (ICA) for nonlinear mixing models. A fundamental difﬁculty in the nonlinear ICA problem is that it is highly nonunique without some extra constraints, which are often realized by using a suitable regularization. We also address the nonlinear blind source separation (BSS) problem. Contrary to the linear case, we consider it different from the respective nonlinear ICA problem. After considering these matters, some methods introduced for solving the nonlinear ICA or BSS problems are discussed in more detail.
The article concludes that increase in service quality of the banks can develop customer satisfaction which ultimately retains valued customers...Keywords: Perceived Service Quality, SERVQUAL, customer satisfaction, BSR, Structural Regression.