An Introduction To Statistical Analysis In Research
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An Introduction To Statistical Analysis In Research
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Author : Kathleen F. Weaver
language : en
Publisher: John Wiley & Sons
Release Date : 2017-09-05
An Introduction To Statistical Analysis In Research written by Kathleen F. Weaver and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-05 with Mathematics categories.
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 Statistics And Data Analysis Using Stata
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Author : Lisa Daniels
language : en
Publisher: SAGE Publications
Release Date : 2019-01-11
An Introduction To Statistics And Data Analysis Using Stata written by Lisa Daniels and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-11 with Social Science categories.
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.
An Introduction To Statistical Learning
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Author : Gareth James
language : en
Publisher: Springer Nature
Release Date : 2023-08-01
An Introduction To Statistical Learning written by Gareth James and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-01 with Mathematics categories.
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.
Analyzing Quantitative Data
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Author : Debra Wetcher-Hendricks
language : en
Publisher: John Wiley & Sons
Release Date : 2014-08-21
Analyzing Quantitative Data written by Debra Wetcher-Hendricks and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-21 with Psychology categories.
A user-friendly, hands-on guide to recognizing and conducting proper research techniques in data collection Offering a unique approach to numerical research methods, Analyzing Quantitative Data: An Introduction for Social Researchers presents readers with the necessary statistical applications for carrying out the key phases of conducting and evaluating a research project. The book guides readers through the steps of data analysis, from organizing raw data to utilizing descriptive statistics and tests of significance, drawing valid conclusions, and writing research reports. The author successfully provides a presentation that is accessible and hands-on rather than heavily theoretical, outlining the key quantitative processes and the use of software to successfully draw valid conclusions from gathered data. In its discussion of methods for organizing data, the book includes suggestions for coding and entry into spreadsheets or databases while also introducing commonly used descriptive statistics and clarifying their roles in data analysis. Next, inferential statistics is explored in-depth with explanations of and instructions for performing chi-square tests, t-tests, analyses of variance, correlation and regression analyses, and a number of advanced statistical procedures. Each chapter contains explanations of when to use the tests described, relevant formulas, and sample computations. The book concludes with guidance on extracting meaningful conclusions from statistical tests and writing research reports that describe procedures and analyses. Throughout the book, Statistical Resources for SPSS® sections provide fundamental instruction for using SPSS® to obtain the results presented. Where necessary, the author provides basic theoretical explanations for distributions and background information regarding formulas. Each chapter concludes with practice problems, and a related website features derivations of the book's formulas along with additional resources for performing the discussed processes. Analyzing Quantitative Data is an excellent book for social sciences courses on data analysis and research methods at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians and practitioners working in the fields of education, medicine, business and public service who analyze, interpret, and evaluate data in their daily work.
Introduction To Statistics And Data Analysis
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Author : Christian Heumann
language : en
Publisher: Springer
Release Date : 2017-01-26
Introduction To Statistics And Data Analysis written by Christian Heumann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-26 with Mathematics categories.
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. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. 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 all methods to their own applications.
An Introduction To Statistical Methods And Data Analysis
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Author : Lyman Ott
language : en
Publisher: Cengage Learning
Release Date : 2010
An Introduction To Statistical Methods And Data Analysis written by Lyman Ott and has been published by Cengage Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematical statistics categories.
Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, 6th Edition, International Edition provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and in news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments.
An Introduction To Statistical Methods Data Analysis
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Author : Lyman Ott
language : en
Publisher:
Release Date : 2016
An Introduction To Statistical Methods Data Analysis written by Lyman Ott and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Mathematical statistics categories.
An Introduction To Data Analysis
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Author : Tiffany Bergin
language : en
Publisher: SAGE
Release Date : 2018-10-15
An Introduction To Data Analysis written by Tiffany Bergin and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-15 with Social Science categories.
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.
An Introduction To Statistical Genetic Data Analysis
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Author : Melinda C. Mills
language : en
Publisher: MIT Press
Release Date : 2020-02-18
An Introduction To Statistical Genetic Data Analysis written by Melinda C. Mills and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-18 with Science categories.
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.
Behavioral Research And Analysis
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Author : Max Vercruyssen
language : en
Publisher: CRC Press
Release Date : 2011-10-19
Behavioral Research And Analysis written by Max Vercruyssen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-19 with Mathematics categories.
Now in its fourth edition, Behavioral Research and Analysis: An Introduction to Statistics within the Context of Experimental Design presents an overview of statistical methods within the context of experimental design. It covers fundamental topics such as data collection, data analysis, interpretation of results, and communication of findings. New in the Fourth Edition: Extensive improvements based on suggestions from those using this book in the classroom Statistical procedures that have been developed and validated since the previous edition Each chapter in the body now contains relevant key words, chapter summaries, key word definitions, and end of chapter exercises (with answers) Revisions to include recent changes in the APA Style Manual When looking for a book for their own use, the authors found none that were totally suitable. They found books that either reviewed the basics of behavioral research and experimental design but provided only cursory coverage of statistical methods or they provided coverage of statistical methods with very little coverage of the research context within which these methods are used. No single resource provided coverage of methodology, statistics, and communication skills. In a classic example of necessity being the mother of invention, the authors created their own. This text is ideal for a single course that reviews research methods, essential statistics through multi-factor analysis of variance, and thesis (or major project) preparation without discussion of derivation of equations, probability theory, or mathematic proofs. It focuses on essential information for getting a research project completed without prerequisite math or statistics training. It has been revised many times to help students at a variety of academic levels (exceptional high school students, undergraduate honors students, masters students, doctoral students, and post-doctoral fellows) across varied academic disciplines (e.g., human factors and ergonomics, behavioral and social sciences, natural sciences, engineering, exercise and sport sciences, business and management, industrial hygiene and safety science, health and medical sciences, and more). Illustrating how to plan, prepare, conduct, and analyze an experimental or research report, the book emphasizes explaining statistical procedures and interpreting obtained results without discussing the derivation of equations or history of the method. Destined to spend more time on your desk than on the shelf, the book will become the single resource you reach for again and again when conducting scientific research and reporting it to the scientific community.