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Author: Dana K. Keller Publisher: SAGE ISBN: 9781412913140 Category : Mathematics Languages : en Pages : 172
Book Description
A new approach to statistics, in plain English, this text explains what statistics mean & how they are used, rather than how to calculate them.
Author: Dana K. Keller Publisher: SAGE ISBN: 9781412913140 Category : Mathematics Languages : en Pages : 172
Book Description
A new approach to statistics, in plain English, this text explains what statistics mean & how they are used, rather than how to calculate them.
Author: Dana K. Keller Publisher: SAGE Publications ISBN: 1452223297 Category : Social Science Languages : en Pages : 161
Book Description
Dana K. Keller and Mary Lou Casadevall-Keller provide readers with a highly accessible introduction to the fundamental concepts of research methods in The Tao of Research: A Path to Validity. This brief, engaging book approaches the topic of research through an exploration of the issues that threaten validity in the process of knowledge generation. Key Features Examines the propositional, ethical, structural, functional, and technical restrictions researchers face Focuses on understanding how these restrictions influence research methods and results Makes concepts more accessible through discussions that follow the experiences of three "guides"—a high school principal, a statewide director of public health, and a sociology professor at a small liberal arts college. The Tao of Research: A Path to Validity serves as either a main or supplemental text for courses such as Introduction to Research Methods, Social Research Methods, and Applied Research Methods.
Author: Ning-Zhong Shi Publisher: World Scientific ISBN: 9812814361 Category : Science Languages : en Pages : 320
Book Description
This book presents up-to-date theory and methods of statistical hypothesis testing based on measure theory. The so-called statistical space is a measurable space adding a family of probability measures. Most topics in the book will be developed based on this term. The book includes some typical data sets, such as the relation between race and the death penalty verdict, the behavior of food intake of two kinds of Zucker rats, and the per capita income and expenditure in China during the 1978?2002 period. Emphasis is given to the process of finding appropriate statistical techniques and methods of evaluating these techniques.
Author: Fred Pyrczak Publisher: Taylor & Francis ISBN: 1351969870 Category : Psychology Languages : en Pages : 185
Book Description
• An overview of descriptive and inferential statistics without formulas and computations. • Clear and to-the-point narrative makes this short book perfect for all courses in which statistics are discussed. • Helps statistics students who are struggling with the concepts. Shows them the meanings of the statistics they are computing. • This book is easy to digest because it is divided into short sections with review questions at the end of each section. • Running sidebars draw students’ attention to important concepts.
Author: Neil Burdess Publisher: SAGE Publications Ltd ISBN: 1446200094 Category : Social Science Languages : en Pages : 202
Book Description
Statistics: A Short, Clear Guide is an accessible, humorous and easy introduction to statistics for social science students. In this refreshing book, experienced author and academic Neil Burdess shows that statistics are not the result of some mysterious "black magic", but rather the result of some very basic arithmetic. Getting rid of confusing x′s and y′s, he shows that it′s the intellectual questions that come before and after the calculations that are important: (i) What are the best statistics to use with your data? and (ii) What do the calculated statistics tell you? Statistics: A Short, Clear Guide aims to help students make sense of the logic of statistics and to decide how best to use statistics to analyse their own data. What′s more, it is not reliant on students having access to any particular kind of statistical software package. This is a very useful book for any student in the social sciences doing a statistics course or needing to do statistics for themselves for the first time.
Author: Arunabh Ghosh Publisher: Princeton University Press ISBN: 0691179476 Category : History Languages : en Pages : 360
Book Description
Revision of author's thesis (doctoral)--Columbia University, 2014, titled Making it count: statistics and state-society relations in the early People's Republic of China, 1949-1959.
Author: David J. Bartholomew Publisher: SAGE ISBN: 1473934338 Category : Social Science Languages : en Pages : 193
Book Description
This is a book about the ideas that drive statistics. It is an ideal primer for students who need an introduction to the concepts of statistics without the added confusion of technical jargon and mathematical language. It introduces the intuitive thinking behind standard procedures, explores the process of informal reasoning, and uses conceptual frameworks to provide a foundation for students new to statistics. It showcases the expertise we have all developed from living in a data saturated society, increases our statistical literacy and gives us the tools needed to approach statistical mathematics with confidence. Key topics include: Variability Standard Distributions Correlation Relationship Sampling Inference An engaging, informal introduction this book sets out the conceptual tools required by anyone undertaking statistical procedures for the first time or for anyone needing a fresh perspective whilst studying the work of others.
Author: Dennis D. Boos Publisher: Springer Science & Business Media ISBN: 1461448182 Category : Mathematics Languages : en Pages : 567
Book Description
This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.
Author: Tao Li Publisher: CRC Press ISBN: 1439835527 Category : Business & Economics Languages : en Pages : 386
Book Description
The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing. The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining. The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.
Author: Dana K. Keller
Author: Dana K. Keller
Author: Dana K. Keller
Author: Ning-Zhong Shi
Author: Dr Dana K Keller
Author: Fred Pyrczak
Author: Neil Burdess
Author: Arunabh Ghosh
Author: David J. Bartholomew
Author: Dennis D. Boos
Author: Tao Li