Advanced Educational Statistics. - Reference Book PDF Download

Author: Prin. Dr. Sushma Thirekar
Publisher: Success Publication
ISBN:
Category : Education
Languages : en
Pages : 228

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Book Description
"Unlock the complexities of educational statistics with 'Statistical Mastery in Education' by Professor Sarah Brown. A comprehensive guide for educators navigating advanced statistical concepts in educational research."

Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446

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Book Description
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.

Author: Eugene Demidenko
Publisher: John Wiley & Sons
ISBN: 1118387988
Category : Mathematics
Languages : en
Pages : 880

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Book Description
Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei, and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth.edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.

Author: Jeremy J Foster
Publisher: SAGE
ISBN: 1412900131
Category : Social Science
Languages : en
Pages : 194

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Book Description
The spread of sophisticated computer packages and the machinery on which to run them has meant that procedures which were previously only available to experienced researchers with access to expensive machines and research students can now be carried out in a few seconds by almost every undergraduate. Understanding and Using Advanced Statistics provides the basis for gaining an understanding of what these analytic procedures do, when they should be used, and what the results provided signify. This comprehensive textbook guides students and researchers through the transition from simple statistics to more complex procedures with accessible language and illustration.

Author: David Diez
Publisher:
ISBN: 9781943450046
Category :
Languages : en
Pages :

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Book Description
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.

Author: Larry Hatcher
Publisher: Shadow Finch Media LLC
ISBN: 9780985867003
Category : Mathematical statistics
Languages : en
Pages : 632

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Book Description
"Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results" is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles. "wwwStatsInResearch.com, " is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors. "Advanced Statistics in Research" does not show how to "perform" statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. "Advanced Statistics in Research" assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples. "Need help writing up your results?" Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more). "Advanced Statistics in Research" is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.

Author: David M Lane
Publisher:
ISBN: 9781687894250
Category :
Languages : en
Pages : 406

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Book Description
Online Statistics: An Interactive Multimedia Course of Study is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.This print edition of the public domain textbook gives the student an opportunity to own a physical copy to help enhance their educational experience. This part I features the book Front Matter, Chapters 1-10, and the full Glossary. Chapters Include:: I. Introduction, II. Graphing Distributions, III. Summarizing Distributions, IV. Describing Bivariate Data, V. Probability, VI. Research Design, VII. Normal Distributions, VIII. Advanced Graphs, IX. Sampling Distributions, and X. Estimation. Online Statistics Education: A Multimedia Course of Study (http: //onlinestatbook.com/). Project Leader: David M. Lane, Rice University.

Author: David Diez
Publisher:
ISBN: 9781500700683
Category :
Languages : en
Pages : 402

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Book Description
A free PDF copy of this textbook may be found on the project's website (do an online search for OpenIntro). This is a Preliminary Edition of a new textbook by OpenIntro that is focused on the advanced high school level.Chapters: 1 - Data Collection,2 - Summarizing Data,3 - Probability,4 - Distributions of Random Variables,5 - Foundation for Inference,6 - Inference for Categorical Data,7 - Inference for Numerical Data,8 - Introduction to Linear Regression.

Author: Mauly Halwat Hikmat
Publisher: Springer Nature
ISBN: 2384760866
Category : Education
Languages : en
Pages : 2656

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Book Description
This is an open access book. The COVID-19 pandemic in the last two years has influenced how educational system works. Online learning became the primal policy taken by all institutions in the world to lower the risk of the virus spread. Despite the drawbacks of the online learning, teachers and students were accustomed with the distant learning through web meetings, Learning Management Systems (LMS) and other online learning platforms. In that time, topics under digital learning and education 5.0 were the main stakes in academic disseminations. This year some institutions start to conduct their teaching and learning process classically as before the pandemic, others are still continuing online and not few are in hybrid. This leaves a question: what learning reform should be made in post-pandemic era? This conference invites researchers, experts, teachers and students to discuss the coping solutions of the question. It is important for them to contribute to the understanding of re-imaging online education for better futures, innovative learning design, new skills for living and working in new times, global challenge of education, learning and teaching with blended learning, flipped learning, integrating life skills for students in the curriculum, developing educators for the future distance learning, humanities learning in the digital era, assessment and measurement in education, challenges and transformations in education, technology in teaching and learning, new learning and teaching models. Not limited to these, scholars may add another interesting topic related to learning reform in post-pandemic era to present.

Author: Biju, Soly Mathew
Publisher: IGI Global
ISBN: 1668486989
Category : Computers
Languages : en
Pages : 321

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Book Description
The world is approaching a point where big data will start to play a beneficial role in many industries and organizations. Today, analyzing data for new insights has become an everyday norm, increasing the need for data analysts to use efficient and appropriate tools to provide quick and valuable results to clients. Existing research in the field currently lacks a full coverage of all essential algorithms, leaving a knowledge void for practical implementation and code in Python with all needed libraries and links to datasets used. Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science serves as a one-stop book to help emerging data scientists gain hands-on skills needed through real-world data and completely up-to-date Python code. It covers all the technical details, from installing the needed software to importing libraries and using the latest data sets; deciding on the right model; training, testing, and evaluating the model; and including NumPy, Pandas, and matplotlib. With coverage on various machine learning algorithms like regression, linear and logical regression, classification, support vector machine (SVM), clustering, k-nearest neighbor, market basket analysis, Apriori, k-means clustering, and visualization using Seaborne, it is designed for academic researchers, undergraduate students, postgraduate students, executive education program leaders, and practitioners.