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Author: Charles P. McKeague
Publisher:
ISBN: 9781630981709
Category : Algebra
Languages : en
Pages :
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Book Description
Author: Charles P. McKeague
Publisher:
ISBN: 9781630981709
Category : Algebra
Languages : en
Pages :
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Book Description
Author: Anna Bargagliotti
Publisher:
ISBN: 9781734223514
Category : Statistics
Languages : en
Pages : 124
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Book Description
"This document lays out a curriculum framework for pre-K-12 educational programs that is designed to help students achieve data literacy and become statistically literate. The framework and subsequent sections in this book recommend curriculum and implementation strategies covering pre-K-12 statistics education"--
Author: Louis Cohen
Publisher: SAGE
ISBN: 1446275787
Category : Social Science
Languages : en
Pages : 388
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Book Description
This bestselling textbook is designed to help students understand parametric and nonparametric statistical methods so that they can tackle research problems successfully. By working through this book carefully and systematically, those who may not have a strong background in mathematics will gain a thorough grasp of the most widely used statistical methods in the social sciences.
Author: M. Kraska-MIller
Publisher: CRC Press
ISBN: 1466507608
Category : Mathematics
Languages : en
Pages : 262
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Book Description
Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM’s SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analyses Discusses the interpretations of statistical results and conclusions of the research With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.
Author: David Williams
Publisher: Cambridge University Press
ISBN: 9780521006187
Category : Mathematics
Languages : en
Pages : 570
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Book Description
An advanced textbook; with many examples and exercises, often with hints or solutions; code is provided for computational examples and simulations.
Author: Robert Szafran
Publisher: SAGE
ISBN: 1412991323
Category : Computers
Languages : en
Pages : 457
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Book Description
"The book is divided into three Parts: Part One has chapters that introduce data analysis and SPSS; Part Two contains eight chapters on descriptive statistics that begin with frequency tables and go through multiple regression; and Part Three includes six chapters on inferential statistics. Part One: Getting Started begins by answering some questions most students have right at the start © questions like why study data analysis and how much math and computer knowledge is required? Essential concepts from research methods relevant for data analysis are also explained. Part Two: Descriptive Statistics: Answering Questions about Your Data demonstrates procedures to use when the analyst is only concerned with describing the cases for which he or she actually has data. Statistics summarizing single variables (univariate statistics) are presented first and then statistics summarizing relationships between variables (multivariate statistics). Frequency tables, measures of central tendency, measures of dispersion, crosstabs, measures of association, subgroup means, and regression are all covered as are bar charts, pie charts, histograms, and clustered bar charts. Part Three: Inferential Statistics: Answering Questions about Populations explains procedures which allow the analyst to draw conclusions about the population from which his or her sample of cases was randomly selected. It begins with a simple chapter on the statistical theory behind inferential statistics. A four-step approach to hypothesis testing is introduced in the next chapter and demonstrated with one-sample t test hypotheses. The remaining chapters present different types of hypothesis tests including paired-samples, independent-samples, one and two-way ANOVA, and chi-square"--Provided by publisher.
Author: Michael R. Hulsizer
Publisher: John Wiley & Sons
ISBN: 9781444305241
Category : Psychology
Languages : en
Pages : 280
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Book Description
A Guide to Teaching Statistics: Innovations and BestPractices addresses the critical aspects of teaching statisticsto undergraduate students, acting as an invaluable tool for bothnovice and seasoned teachers of statistics. Guidance on textbook selection, syllabus construction, andcourse outline Classroom exercises, computer applications, and Internetresources designed to promote active learning Tips for incorporating real data into course content Recommendations on integrating ethics and diversity topics intostatistics education Strategies to assess student's statistical literacy, thinking,and reasoning skills Additional material online at ahref="http://www.teachstats.org/"www.teachstats.org/a
Author: United States. Superintendent of Documents
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 388
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Book Description
Author: Mark Louis Taper
Publisher: Frontiers Media SA
ISBN: 288974406X
Category : Science
Languages : en
Pages : 238
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Book Description
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.
