Intermediate Statistical Investigations

Intermediate Statistical Investigations

Author: Nathan Tintle

Publisher: John Wiley & Sons

Published: 2020-09-09

Total Pages: 608

ISBN-13: 1119634520

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Intermediate Statistical Investigations provides a unified framework for explaining variation across study designs and variable types, helping students increase their statistical literacy and appreciate the indispensable role of statistics in scientific research. Requiring only a single introductory statistics course as a prerequisite, the program uses the immersive, simulation-based inference approach for which the author team is known.Students engage with various aspects of data collection and analysis using real examples and clear explanations designed to strengthen multivariable understanding and reinforce first-course concepts. Each chapter contains in-depth exercises which follow a consistent six-step statistical exploration and investigation method (ask a research question, design a study, explore the data, draw inferences, formulate conclusions, and look back and ahead) enabling students to assess a variety of concepts in a single assignment. Challenging questions based on research articles strengthen critical reading skills, fully worked examples demonstrate essential concepts and methods, and engaging visualizations illustrate key themes of explained variation. End-of-chapter investigations use real data from popular culture and published research studies in a variety of disciplines, exposing students to various applications of statistics in the real world. Throughout the text, user-friendly Rossman Chance web applets allow students to conduct the simulations and analyses covered in the book.


Introduction to Statistical Investigations

Introduction to Statistical Investigations

Author: Nathan Tintle

Publisher: Wiley Global Education

Published: 2015-12-17

Total Pages: 699

ISBN-13: 1119154316

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Introduction to Statistical Investigations leads students to learn about the process of conducting statistical investigations from data collection, to exploring data, to statistical inference, to drawing appropriate conclusions. The text is designed for a one-semester introductory statistics course. It focuses on genuine research studies, active learning, and effective use of technology. Simulations and randomization tests introduce statistical inference, yielding a strong conceptual foundation that bridges students to theory-based inference approaches. Repetition allows students to see the logic and scope of inference. This implementation follows the GAISE recommendations endorsed by the American Statistical Association.


Statistical Power Analysis for the Behavioral Sciences

Statistical Power Analysis for the Behavioral Sciences

Author: Jacob Cohen

Publisher: Routledge

Published: 2013-05-13

Total Pages: 625

ISBN-13: 1134742770

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Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.


Introduction to Statistical Investigations

Introduction to Statistical Investigations

Author: Nathan Tintle

Publisher: John Wiley & Sons

Published: 2020-09-16

Total Pages: 143

ISBN-13: 1119683459

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Introduction to Statistical Investigations, Second Edition provides a unified framework for explaining variation across study designs and variable types, helping students increase their statistical literacy and appreciate the indispensable role of statistics in scientific research. Requiring only basic algebra as a prerequisite, the program uses the immersive, simulation-based inference approach for which the author team is known. Students engage with various aspects of data collection and analysis using real data and clear explanations designed to strengthen multivariable understanding and reinforce concepts. Each chapter follows a coherent six-step statistical exploration and investigation method (ask a research question, design a study, explore the data, draw inferences, formulate conclusions, and look back and ahead) enabling students to assess a variety of concepts in a single assignment. Challenging questions based on research articles strengthen critical reading skills, fully worked examples demonstrate essential concepts and methods, and engaging visualizations illustrate key themes of explained variation. The end-of-chapter investigations expose students to various applications of statistics in the real world using real data from popular culture and published research studies in variety of disciplines. Accompanying examples throughout the text, user-friendly applets enable students to conduct the simulations and analyses covered in the book.


Practicing Statistics

Practicing Statistics

Author: Shonda Kuiper

Publisher:

Published: 2013

Total Pages: 0

ISBN-13: 9780321586018

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Building on the introductory course, Practicing Statistics: Guided Investigations for the Second Course presents a variety of compelling topics for a second course in statistics, such as multiple regression, nonparametric methods, and survival analysis. Every topic is introduced in the context of a real-world research question, asking students to explore the concepts firsthand with guided activities and research projects. The number of students taking AP Statistics continues to rise, and the number of students taking an introductory statistics course has more than doubled since 1990. As a result, the goals of the second course have changed. This course must engage students from multiple disciplines and demonstrate the broad applicability of statistics to their lives. To that end, this text takes an inquiry-based approach that teaches advanced statistical techniques through group work and hands-on exploration using real research questions. The chapters are modular, so that instructors can select only the topics relevant to their course, and teach them in any order. The only prerequisite is an algebra-based introductory statistics or AP statistics course.


Intermediate Statistics Using SPSS

Intermediate Statistics Using SPSS

Author: Herschel Knapp

Publisher: SAGE Publications

Published: 2017-09-14

Total Pages: 381

ISBN-13: 1506377416

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What statistical test should I use for this kind of data? How do I set up the data? What parameters should I specify when ordering the test? How do I interpret the results? Herschel Knapp′s friendly and approachable guide to real-world statistics answers these questions. Intermediate Statistics Using SPSS is not about abstract statistical theory or the derivation or memorization of statistical formulas–it is about applied statistics. With jargon-free language and clear processing instructions, this text covers the most common statistical functions–from basic to more advanced. Practical exercises at the conclusion of each chapter offer students an opportunity to process viable data sets, write cohesive abstracts in APA style, and build a thorough comprehension of the statistical process. Students will learn by doing with this truly practical approach to statistics.


Introduction to Probability and Statistics Using R

Introduction to Probability and Statistics Using R

Author: G. Jay Kerns

Publisher: Lulu.com

Published: 2010-01-10

Total Pages: 388

ISBN-13: 0557249791

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This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.


The Book of R

The Book of R

Author: Tilman M. Davies

Publisher: No Starch Press

Published: 2016-07-16

Total Pages: 833

ISBN-13: 1593276516

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The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.