An Introduction To Statistical Analysis In Research

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An Introduction to Statistical Analysis in Research, Optimized Edition

Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Kanya Godde,Pablo F. Weaver
An Introduction to Statistical Analysis in Research Optimized Edition Book PDF

Author : Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Kanya Godde,Pablo F. Weaver
Publisher : John Wiley & Sons
Page : 616 pages
File Size : 41,6 Mb
Release : 2017-08-10
Category : Mathematics
ISBN : 9781119301103

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An Introduction to Statistical Analysis in Research, Optimized Edition by Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Kanya Godde,Pablo F. Weaver Pdf

Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS®, Excel®, and Numbers® output An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages including R, SPSS®, Excel®, and Numbers®. Specific emphasis is on the practical application of statistics in the biological and life sciences, while enhancing reader skills in identifying the research questions and testable hypotheses, determining the appropriate experimental methodology and statistical analyses, processing data, and reporting the research outcomes. In addition, this book: • Aims to develop readers’ skills including how to report research outcomes, determine the appropriate experimental methodology and statistical analysis, and identify the needed research questions and testable hypotheses • Includes pedagogical elements throughout that enhance the overall learning experience including case studies and tutorials, all in an effort to gain full comprehension of designing an experiment, considering biases and uncontrolled variables, analyzing data, and applying the appropriate statistical application with valid justification • Fills the gap between theoretically driven, mathematically heavy texts and introductory, step-by-step type books while preparing readers with the programming skills needed to carry out basic statistical tests, build support figures, and interpret the results • Provides a companion website that features related R, SPSS, Excel, and Numbers data sets, sample PowerPoint® lecture slides, end of the chapter review questions, software video tutorials that highlight basic statistical concepts, and a student workbook and instructor manual An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences is an ideal textbook for upper-undergraduate and graduate-level courses in research methods, biostatistics, statistics, biology, kinesiology, sports science and medicine, health and physical education, medicine, and nutrition. The book is also appropriate as a reference for researchers and professionals in the fields of anthropology, sports research, sports science, and physical education. KATHLEEN F. WEAVER, PhD, is Associate Dean of Learning, Innovation, and Teaching and Professor in the Department of Biology at the University of La Verne. The author of numerous journal articles, she received her PhD in Ecology and Evolutionary Biology from the University of Colorado. VANESSA C. MORALES, BS, is Assistant Director of the Academic Success Center at the University of La Verne. SARAH L. DUNN, PhD, is Associate Professor in the Department of Kinesiology at the University of La Verne and is Director of Research and Sponsored Programs. She has authored numerous journal articles and received her PhD in Health and Exercise Science from the University of New South Wales. KANYA GODDE, PhD, is Assistant Professor in the Department of Anthropology and is Director/Chair of Institutional Review Board at the University of La Verne. The author of numerous j

An Introduction to Statistical Analysis in Research

Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Kanya Godde,Pablo F. Weaver
An Introduction to Statistical Analysis in Research Book PDF

Author : Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Kanya Godde,Pablo F. Weaver
Publisher : John Wiley & Sons
Page : 608 pages
File Size : 50,8 Mb
Release : 2017-09-05
Category : Mathematics
ISBN : 9781119299684

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An Introduction to Statistical Analysis in Research by Kathleen F. Weaver,Vanessa C. Morales,Sarah L. Dunn,Kanya Godde,Pablo F. Weaver Pdf

Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS®, Excel®, and Numbers® output An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages including R, SPSS®, Excel®, and Numbers®. Specific emphasis is on the practical application of statistics in the biological and life sciences, while enhancing reader skills in identifying the research questions and testable hypotheses, determining the appropriate experimental methodology and statistical analyses, processing data, and reporting the research outcomes. In addition, this book: • Aims to develop readers’ skills including how to report research outcomes, determine the appropriate experimental methodology and statistical analysis, and identify the needed research questions and testable hypotheses • Includes pedagogical elements throughout that enhance the overall learning experience including case studies and tutorials, all in an effort to gain full comprehension of designing an experiment, considering biases and uncontrolled variables, analyzing data, and applying the appropriate statistical application with valid justification • Fills the gap between theoretically driven, mathematically heavy texts and introductory, step-by-step type books while preparing readers with the programming skills needed to carry out basic statistical tests, build support figures, and interpret the results • Provides a companion website that features related R, SPSS, Excel, and Numbers data sets, sample PowerPoint® lecture slides, end of the chapter review questions, software video tutorials that highlight basic statistical concepts, and a student workbook and instructor manual An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences is an ideal textbook for upper-undergraduate and graduate-level courses in research methods, biostatistics, statistics, biology, kinesiology, sports science and medicine, health and physical education, medicine, and nutrition. The book is also appropriate as a reference for researchers and professionals in the fields of anthropology, sports research, sports science, and physical education. KATHLEEN F. WEAVER, PhD, is Associate Dean of Learning, Innovation, and Teaching and Professor in the Department of Biology at the University of La Verne. The author of numerous journal articles, she received her PhD in Ecology and Evolutionary Biology from the University of Colorado. VANESSA C. MORALES, BS, is Assistant Director of the Academic Success Center at the University of La Verne. SARAH L. DUNN, PhD, is Associate Professor in the Department of Kinesiology at the University of La Verne and is Director of Research and Sponsored Programs. She has authored numerous journal articles and received her PhD in Health and Exercise Science from the University of New South Wales. KANYA GODDE, PhD, is Assistant Professor in the Department of Anthropology and is Director/Chair of Institutional Review Board at the University of La Verne. The author of numerous journal articles and a member of the American Statistical Association, she received her PhD in Anthropology from the University of Tennessee. PABLO F. WEAVER, PhD, is Instructor in the Department of Biology at the University of La Verne. The author of numerous journal articles, he received his PhD in Ecology and Evolutionary Biology from the University of Colorado.

An Introduction to Statistical Genetic Data Analysis

Melinda C. Mills,Nicola Barban,Felix C. Tropf
An Introduction to Statistical Genetic Data Analysis Book PDF

Author : Melinda C. Mills,Nicola Barban,Felix C. Tropf
Publisher : MIT Press
Page : 433 pages
File Size : 53,5 Mb
Release : 2020-02-18
Category : Science
ISBN : 9780262357449

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An Introduction to Statistical Genetic Data Analysis by Melinda C. Mills,Nicola Barban,Felix C. Tropf Pdf

A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.

Introduction to Statistical Analysis of Laboratory Data

Alfred Bartolucci,Karan P. Singh,Sejong Bae
Introduction to Statistical Analysis of Laboratory Data Book PDF

Author : Alfred Bartolucci,Karan P. Singh,Sejong Bae
Publisher : John Wiley & Sons
Page : 259 pages
File Size : 40,5 Mb
Release : 2015-12-02
Category : Mathematics
ISBN : 9781118736869

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Introduction to Statistical Analysis of Laboratory Data by Alfred Bartolucci,Karan P. Singh,Sejong Bae Pdf

Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process Introduces terminology used in many applications such as the interpretation of assay design and validation as well as “fit for purpose” procedures including real world examples Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions

An Introduction to Statistics and Data Analysis Using Stata®

Lisa Daniels,Nicholas Minot
An Introduction to Statistics and Data Analysis Using Stata Book PDF

Author : Lisa Daniels,Nicholas Minot
Publisher : SAGE Publications
Page : 513 pages
File Size : 42,7 Mb
Release : 2019-01-11
Category : Social Science
ISBN : 9781506371825

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An Introduction to Statistics and Data Analysis Using Stata® by Lisa Daniels,Nicholas Minot Pdf

An Introduction to Statistics and Data Analysis Using Stata® by Lisa Daniels and Nicholas Minot provides a step-by-step introduction for statistics, data analysis, or research methods classes with Stata. Concise descriptions emphasize the concepts behind statistics for students rather than the derivations of the formulas. With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.

Introduction to Statistics and Data Analysis

Christian Heumann,Michael Schomaker,Shalabh
Introduction to Statistics and Data Analysis Book PDF

Author : Christian Heumann,Michael Schomaker,Shalabh
Publisher : Springer Nature
Page : 584 pages
File Size : 43,8 Mb
Release : 2023-01-30
Category : Mathematics
ISBN : 9783031118333

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Introduction to Statistics and Data Analysis by Christian Heumann,Michael Schomaker,Shalabh Pdf

Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.

Introduction to Statistics

Howard M. Reid
Introduction to Statistics Book PDF

Author : Howard M. Reid
Publisher : SAGE Publications
Page : 633 pages
File Size : 48,5 Mb
Release : 2013-08-13
Category : Social Science
ISBN : 9781483301570

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Introduction to Statistics by Howard M. Reid Pdf

Using a truly accessible and reader-friendly approach, Introduction to Statistics: Fundamental Concepts and Procedures of Data Analysis, by Howard M. Reid, redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.

An Introduction to Statistical Learning

Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor
An Introduction to Statistical Learning Book PDF

Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor
Publisher : Springer Nature
Page : 617 pages
File Size : 43,8 Mb
Release : 2023-08-01
Category : Mathematics
ISBN : 9783031387470

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An Introduction to Statistical Learning by Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor Pdf

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

An Introduction to Statistical Methods and Data Analysis

R. Lyman Ott,Micheal Longnecker
An Introduction to Statistical Methods and Data Analysis Book PDF

Author : R. Lyman Ott,Micheal Longnecker
Publisher : Cengage Learning
Page : 0 pages
File Size : 46,5 Mb
Release : 2010-02-16
Category : Probabilities
ISBN : 0495109150

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An Introduction to Statistical Methods and Data Analysis by R. Lyman Ott,Micheal Longnecker Pdf

Provides worked-out solutions to odd-numbered exercises.

Introduction to Statistical Mediation Analysis

David MacKinnon
Introduction to Statistical Mediation Analysis Book PDF

Author : David MacKinnon
Publisher : Routledge
Page : 488 pages
File Size : 44,5 Mb
Release : 2012-10-02
Category : Medical
ISBN : 9781136676130

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Introduction to Statistical Mediation Analysis by David MacKinnon Pdf

This volume introduces the statistical, methodological, and conceptual aspects of mediation analysis. Applications from health, social, and developmental psychology, sociology, communication, exercise science, and epidemiology are emphasized throughout. Single-mediator, multilevel, and longitudinal models are reviewed. The author's goal is to help the reader apply mediation analysis to their own data and understand its limitations. Each chapter features an overview, numerous worked examples, a summary, and exercises (with answers to the odd numbered questions). The accompanying CD contains outputs described in the book from SAS, SPSS, LISREL, EQS, MPLUS, and CALIS, and a program to simulate the model. The notation used is consistent with existing literature on mediation in psychology. The book opens with a review of the types of research questions the mediation model addresses. Part II describes the estimation of mediation effects including assumptions, statistical tests, and the construction of confidence limits. Advanced models including mediation in path analysis, longitudinal models, multilevel data, categorical variables, and mediation in the context of moderation are then described. The book closes with a discussion of the limits of mediation analysis, additional approaches to identifying mediating variables, and future directions. Introduction to Statistical Mediation Analysis is intended for researchers and advanced students in health, social, clinical, and developmental psychology as well as communication, public health, nursing, epidemiology, and sociology. Some exposure to a graduate level research methods or statistics course is assumed. The overview of mediation analysis and the guidelines for conducting a mediation analysis will be appreciated by all readers.

Statistical Analysis and Data Display

Richard M. Heiberger,Burt Holland
Statistical Analysis and Data Display Book PDF

Author : Richard M. Heiberger,Burt Holland
Publisher : Springer Science & Business Media
Page : 739 pages
File Size : 49,7 Mb
Release : 2013-06-29
Category : Mathematics
ISBN : 9781475742848

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Statistical Analysis and Data Display by Richard M. Heiberger,Burt Holland Pdf

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.

Research Design & Statistical Analysis

Arnold D. Well,Jerome L. Myers
Research Design Statistical Analysis Book PDF

Author : Arnold D. Well,Jerome L. Myers
Publisher : Psychology Press
Page : 871 pages
File Size : 41,6 Mb
Release : 2003-01-30
Category : Mathematics
ISBN : 9781135641085

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Research Design & Statistical Analysis by Arnold D. Well,Jerome L. Myers Pdf

"Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover

Statistical Methods for Data Analysis in Particle Physics

Luca Lista
Statistical Methods for Data Analysis in Particle Physics Book PDF

Author : Luca Lista
Publisher : Springer
Page : 257 pages
File Size : 51,7 Mb
Release : 2017-10-13
Category : Science
ISBN : 9783319628400

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Statistical Methods for Data Analysis in Particle Physics by Luca Lista Pdf

This concise set of course-based notes provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP). First, the book provides an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on both discoveries and upper limits, as many applications in HEP concern hypothesis testing, where the main goal is often to provide better and better limits so as to eventually be able to distinguish between competing hypotheses, or to rule out some of them altogether. Many worked-out examples will help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical concepts to actual data. This new second edition significantly expands on the original material, with more background content (e.g. the Markov Chain Monte Carlo method, best linear unbiased estimator), applications (unfolding and regularization procedures, control regions and simultaneous fits, machine learning concepts) and examples (e.g. look-elsewhere effect calculation).

An Introduction to Data Analysis

Tiffany Bergin
An Introduction to Data Analysis Book PDF

Author : Tiffany Bergin
Publisher : SAGE
Page : 381 pages
File Size : 53,8 Mb
Release : 2018-10-15
Category : Social Science
ISBN : 9781526452313

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An Introduction to Data Analysis by Tiffany Bergin Pdf

Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis. Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques for conducting quantitative, qualitative, and mixed methods data analysis. With an easy-to-follow organization and clear, jargon-free language, it helps readers not only become proficient data analysts, but also develop the critical thinking skills necessary to assess analyses presented by others in both academic research and the popular media. It includes advice on: - Data analysis frameworks - Validity and credibility of data - Sampling techniques - Data management - The big data phenomenon - Data visualisation - Effective data communication Whether you are new to data analysis or looking for a quick-reference guide to key principles of the process, this book will help you uncover nuances, complexities, patterns, and relationships among all types of data.

Statistical Analysis of Geographical Data

Simon James Dadson
Statistical Analysis of Geographical Data Book PDF

Author : Simon James Dadson
Publisher : John Wiley & Sons
Page : 264 pages
File Size : 53,7 Mb
Release : 2017-03-14
Category : Science
ISBN : 9781118525111

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Statistical Analysis of Geographical Data by Simon James Dadson Pdf

Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.