Sawyer Thomas, Nebl Patrick, Hollis-Sawyer Lisa Black Belt Statistics: A Competency-Based Approach (Plus SPSS and R) 9781516587261

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Автор: Sawyer Thomas, Nebl Patrick, Hollis-Sawyer Lisa
Название: Black Belt Statistics: A Competency-Based Approach (Plus SPSS and R)
ISBN: 9781516587261
Издательство: Mare Nostrum (Eurospan)
Классификация:

Социальные исследования и статистика

ISBN-10: 151658726X
Обложка/Формат: Paperback
Страницы: 240
Вес: 0.42 кг.
Дата издания: 30.04.2020
Язык: English
Размер: 25.40 x 17.81 x 1.30 cm
Ключевые слова: Social research & statistics
Подзаголовок: A competency-based approach (plus spss and r)
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Поставляется из: Англии
Описание: Black Belt Statistics: A Competency-Based Approach (Plus SPSS and R) clearly communicates statistical competencies to students, allows for practice and evaluation, and arranges competencies in a hierarchy. The workbook employs a martial arts-inspired belt system, awarding students new achievement ranks after theyve demonstrated mastery of key concepts and allowing them to proceed to the next level of competencies.The workbook features 11 chapters, each of which represent a belt and proceed in ascending order from white belt to black belt. Opening chapters address basic terminology, resolving formulas, rounding figures, research designs and variables, scales of measurement, and frequency tables and graphs. In later chapters, students learn about central tendency, bivariate correlation and scatterplots, basic probability, hypothesis testing, and z and t tests. More advanced chapters cover confidence intervals, ANOVA, simple regression, Chi-Square, choosing the appropriate test, and SPSS and R programming.Designed to help students at all levels develop statistical skills and a sound knowledge base, Black Belt Statistics is an ideal supplementary workbook for courses in social science statistics and statistical methods at the undergraduate and graduate levels.
Дополнительное описание: Social research and statistics

Black Belt Statistics: A Competency-Based Approach (Plus SPSS and R), Sawyer Thomas, Nebl Patrick, Hollis-Sawyer Lisa