Statistics Plain And Simple
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Author | : Sherri L. Jackson |
Publisher | : Cengage Learning |
Total Pages | : 0 |
Release | : 2016-01-01 |
Genre | : Education |
ISBN | : 9781305638907 |
Sherri Jackson's straightforward, conversational introduction to statistics presents just what its title promises -- a plain and simple overview of statistics that is clear, concise, and sparing in its use of jargon. Ideal for behavioral sciences majors, STATISTICS PLAIN AND SIMPLE, Fourth Edition, is designed to build students' confidence in understanding, calculating, and interpreting statistics. It instills a strong awareness of the interaction between statistical methods and research methods. It also helps students develop a solid working knowledge of basic statistical cautions in research design, a strong understanding of the concept of significance, and the critical thinking skills necessary to apply these ideas. A modular format presents the material in brief segments that make concepts manageable. Jackson shows why each statistical technique is necessary before explaining it, and skillfully uses narrative to connect one module to the next. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Author | : Timothy C. Urdan |
Publisher | : Psychology Press |
Total Pages | : 199 |
Release | : 2005 |
Genre | : Electronic books |
ISBN | : 0805852417 |
This book is meant to be a supplement to a more detailed statistics textbook, such as that recommended for a statistics course in the social sciences. Also, as a reference book to refresh your memory about statistical concepts.
Author | : Thomas Ilvento |
Publisher | : |
Total Pages | : 406 |
Release | : 2013-08-12 |
Genre | : Mathematics |
ISBN | : 9781465204455 |
Author | : Neil J. Salkind |
Publisher | : SAGE Publications |
Total Pages | : 620 |
Release | : 2016-01-29 |
Genre | : Social Science |
ISBN | : 1483374106 |
Based on Neil J. Salkind’s bestselling text, Statistics for People Who (Think They) Hate Statistics, this adapted Excel 2016 version presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Researchers and students uncomfortable with the analysis portion of their work will appreciate the book′s unhurried pace and thorough, friendly presentation. Opening with an introduction to Excel 2016, including functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques and then walks them through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. New to the Fourth Edition: A new chapter 20 dealing with large data sets using Excel functions and pivot tables, and illustrating how certain databases and other categories of functions and formulas can help make the data in big data sets easier to work with and the results more understandable. New chapter-ending exercises are included and contain a variety of levels of application. Additional TechTalks have been added to help students master Excel 2016. A new, chapter-ending Real World Stats feature shows readers how statistics is applied in the everyday world. Basic maths instruction and practice exercises for those who need to brush up on their math skills are included in the appendix.
Author | : Gary M. Klass |
Publisher | : Rowman & Littlefield Publishers |
Total Pages | : 203 |
Release | : 2012-04-13 |
Genre | : Political Science |
ISBN | : 1442215097 |
Just Plain Data Analysis teaches students statistical literacy skills that they can use to evaluate and construct arguments about public affairs issues grounded in numerical evidence. The book addresses skills that are often not taught in introductory social science research methods courses and that are often covered sketchily in the research methods textbooks: where to find commonly used measures of political and social conditions; how to assess the reliability and validity of specific indicators; how to present data efficiently in charts and tables; how to avoid common misinterpretations and misrepresentations of data; and how to evaluate causal arguments based on numerical data. With a new chapter on statistical fallacies and updates throughout the text, the new edition teaches students how to find, interpret, and present commonly used social indicators in an even clearer and more practical way.
Author | : Sherri L. Jackson |
Publisher | : Cengage Learning |
Total Pages | : 400 |
Release | : 2009-08-26 |
Genre | : Education |
ISBN | : 9780495808909 |
Sherri Jackson’s straightforward, conversational introduction to statistics presents just what its title promises -- a plain-and-simple overview of statistics that is clear, concise, and sparing in its use of jargon. Ideal for behavioral sciences majors who need to grasp basic concepts quickly, Jackson’s text is designed to quickly build students’ confidence in understanding, calculating, and interpreting statistics. It instills a strong awareness of the interaction between statistical methods and research methods. It also provides a solid working knowledge of basic statistical cautions in research design, a strong understanding of the concept of significance, and the critical thinking skills necessary to apply these ideas. This paperback book’s modular format (22 modules across 10 chapters) chunks the material into small segments that make even difficult concepts manageable. Jackson shows why each new statistical technique is necessary before explaining it, and skillfully uses narrative to connect one module to the next. The end of each module features a summary review table, Critical Thinking Check items (with answers) review of key terms, and Module Exercises to help students master key concepts. At the end of each chapter, a detailed self-test lets students check their understanding of the concepts. These pedagogical features are a perfect complement to Jackson’s narrative, as they serve to further build students’ confidence with statistical ideas. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Author | : Gareth James |
Publisher | : Springer Nature |
Total Pages | : 617 |
Release | : 2023-08-01 |
Genre | : Mathematics |
ISBN | : 3031387473 |
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.
Author | : Larry Wasserman |
Publisher | : Springer Science & Business Media |
Total Pages | : 446 |
Release | : 2013-12-11 |
Genre | : Mathematics |
ISBN | : 0387217363 |
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 | : Steven R. Terrell |
Publisher | : Guilford Press |
Total Pages | : 429 |
Release | : 2012-03-29 |
Genre | : Social Science |
ISBN | : 1462503233 |
This book has been replaced by Statistics Translated, Second Edition, ISBN 978-1-4625-4540-7.
Author | : Richard C. Sprinthall |
Publisher | : Pearson Higher Ed |
Total Pages | : 646 |
Release | : 2013-10-03 |
Genre | : Social Science |
ISBN | : 1292055510 |
The material in this user-friendly text is presented as simply as possible to ensure that students will gain a solid understanding of statistical procedures and analysis. The goal of this book is to demystify and present statistics in a clear, cohesive manner. The student is presented with rules of evidence and the logic behind those rules. The book is divided into three major units: Descriptive Statistics, Inferential Statistics, and Advanced Topics in Inferential Statistics. Every effort has been made to keep the writing as clear as possible and always aimed at the student's life space. Computational procedures are laid out in a step-by-step, programmed format. This is a straightforward presentation of the essentials of statistical analysis emphasizing the constant interaction between statistical techniques and the resarch methodology.