Estimation And Inferential Statistics PDF Download
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Author | : Pradip Kumar Sahu |
Publisher | : Springer |
Total Pages | : 335 |
Release | : 2015-11-03 |
Genre | : Mathematics |
ISBN | : 8132225147 |
Download Estimation and Inferential Statistics Book in PDF, ePub and Kindle
This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. Every concept is supported with relevant research examples to help readers to find the most suitable application. Statistical tools have been presented by using real-life examples, removing the “fear factor” usually associated with this complex subject. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.
Author | : Jack Fitzgerald |
Publisher | : SAGE Publications |
Total Pages | : 609 |
Release | : 2013-01-17 |
Genre | : Social Science |
ISBN | : 1452292167 |
Download Statistics for Criminal Justice and Criminology in Practice and Research Book in PDF, ePub and Kindle
Statistics for Criminal Justice and Criminology in Practice and Research—by Jack Fitzgerald and Jerry Fitzgerald—is an engaging and comprehensive introduction to the study of basic statistics for students pursuing careers as practitioners or researchers in both Criminal Justice and Criminology programs. This student-friendly text shows how to calculate a variety of descriptive and inferential statistics, recognize which statistics are appropriate for particular data analysis situations, and perform hypothesis tests using inferential statistics. But it is much more than a "cook book." It encourages readers to think critically about the strengths and limitations of the statistics they are calculating, as well as how they may be misapplied and misleading. Examples of statistics and statistical analyses are drawn from the worlds of the practitioner as well as the policymaker and researcher. Students will also gain a clear understanding of major ethical issues in conducting statistical analyses and reporting results, as well as insight into the realities of the life of researchers and practitioners as they use statistics and statistical analyses in their day-to-day activities.
Author | : Halbert White |
Publisher | : Cambridge University Press |
Total Pages | : 396 |
Release | : 1996-06-28 |
Genre | : Business & Economics |
ISBN | : 9780521574464 |
Download Estimation, Inference and Specification Analysis Book in PDF, ePub and Kindle
This book examines the consequences of misspecifications for the interpretation of likelihood-based methods of statistical estimation and interference. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated.
Author | : Malcolm O. Asadoorian |
Publisher | : University Press of America |
Total Pages | : 304 |
Release | : 2005 |
Genre | : Business & Economics |
ISBN | : 9780761830306 |
Download Essentials of Inferential Statistics Book in PDF, ePub and Kindle
Essentials of Inferential Statistics, fourth edition is appropriate for a one semester first course in Applied Statistics or as a reference book for practicing researchers in a wide variety of disciplines, including medicine, natural and social sciences, law, and engineering. Most importantly, this practical book thoroughly describes the Bayesian principles necessary for applied clinical research and strategic interaction, which are frequently omitted in other texts. After a comprehensive treatment of probability theory concepts, theorems, and some basic proofs, this laconically written text illustrates sampling distributions and their importance in estimation for the purpose of statistical inference. The book then shifts its focus to the essentials associated with confidence intervals, and hypothesis testing for major population parameters, namely, the population mean, population variance, and population proportion. In addition, it thoroughly describes the basics of correlation and simple linear regression as well as non-parametric statistics.
Author | : Geoff Cumming |
Publisher | : Taylor & Francis |
Total Pages | : 611 |
Release | : 2024-03-21 |
Genre | : Psychology |
ISBN | : 1003849016 |
Download Introduction to the New Statistics Book in PDF, ePub and Kindle
This fully revised and updated second edition is an essential introduction to inferential statistics. It is the first introductory statistics text to use an estimation approach from the start and also to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. The estimation approach, with meta-analysis (“the new statistics”), is exactly what’s needed for Open Science. Key features of this new edition include: Even greater prominence for Open Science throughout the book. Students easily understand basic Open Science practices and are guided to use them in their own work. There is discussion of the latest developments now being widely adopted across science and medicine. Integration of new open-source esci (Estimation Statistics with Confidence Intervals) software, running in jamovi. This is ideal for the book and extends seamlessly to what’s required for more advanced courses, and also by researchers. See www.thenewstatistics.com/itns/esci/jesci/. Colorful interactive simulations, including the famous dances, to help make key statistical ideas intuitive. These are now freely available through any browser. See www.esci.thenewstatistics.com/. Coverage of both estimation and null hypothesis significance testing (NHST) approaches, with full guidance on how to translate between the two. Effective learning strategies and pedagogical features to promote critical thinking, comprehension and retention Designed for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding Open Science and the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.
Author | : Sue L. T. McGregor |
Publisher | : SAGE Publications |
Total Pages | : 880 |
Release | : 2017-10-25 |
Genre | : Social Science |
ISBN | : 1506350976 |
Download Understanding and Evaluating Research Book in PDF, ePub and Kindle
Understanding and Evaluating Research: A Critical Guide shows students how to be critical consumers of research and to appreciate the power of methodology as it shapes the research question, the use of theory in the study, the methods used, and how the outcomes are reported. The book starts with what it means to be a critical and uncritical reader of research, followed by a detailed chapter on methodology, and then proceeds to a discussion of each component of a research article as it is informed by the methodology. The book encourages readers to select an article from their discipline, learning along the way how to assess each component of the article and come to a judgment of its rigor or quality as a scholarly report.
Author | : L E MacCarter |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 568 |
Release | : 2021-07-19 |
Genre | : |
ISBN | : 9781532721076 |
Download Research Decisions and Estimation With Confidence and Power Book in PDF, ePub and Kindle
Research Decisions and Estimation with Confidence and Power: This book is about research with an emphasis on inference, sample size, confidence intervals, and a rational approach to power, offered at an affordable price for students everywhere. It explores current controversies in inferential statistics. It deals with sample size estimation for a wide variety of experimental situations. An updated general statistics text/reference that emphasizes the latest approaches to a priori sample size and power Can be used as a text for majors or non-majors in statistics, as a curriculum for any level of statistical training, or as a reference for researchers 560+ pages at a price researchers and students anywhere can afford New material researched from classical and recent literature (extensive citations and index) Avoids the use of the unfortunately common "large," "medium," and "small," which has been discredited for decades, including by the tacit admission of its author, Cohen (1988, p25) Discusses ways to avoid pitfalls due to the lack of robustness of the ANOVA, the fact that data is almost never normal etc.
Author | : Ayanendranath Basu |
Publisher | : CRC Press |
Total Pages | : 424 |
Release | : 2011-06-22 |
Genre | : Computers |
ISBN | : 1420099663 |
Download Statistical Inference Book in PDF, ePub and Kindle
In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Stati
Author | : Sharmishtha Kulkarni Ph D |
Publisher | : |
Total Pages | : 254 |
Release | : 2020-11-11 |
Genre | : |
ISBN | : |
Download Statistical Inference Book in PDF, ePub and Kindle
The book provides an insight into elementary inferential statistical methodologies including point estimation, interval estimation, and parametric and nonparametric tests. With a substantial emphasis on conceptual knowledge, the book provides working methodologies with sufficient number of illustrative examplesThis book focuses on the meaning of statistical inference on point estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out practical examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.This book offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the concepts of point estimation and properties of point estimation as unbiasedness, consistency, sufficiency, relative efficiency. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course.KEY FEATURES1.Easy to understand, completely solved Problems of point estimation and its properties 2.Provides of clarification for number of steps in the proof of theorems and related results 3.Includes numerous solved examples to illustrate the application of theorems and results4.It improves the analytical insights of respondentsEvery concept is supported with relevant research examples to help readers to find the most suitable application
Author | : Larry Wasserman |
Publisher | : Springer Science & Business Media |
Total Pages | : 446 |
Release | : 2013-12-11 |
Genre | : Mathematics |
ISBN | : 0387217363 |
Download All of Statistics Book in PDF, ePub and Kindle
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.