Introductory Applied Statistics: With Resampling Methods & R - Brossura

Blaine, Bruce

 
9783031277436: Introductory Applied Statistics: With Resampling Methods & R

Sinossi

This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods. It covers robust and non-robust descriptive statistics used in each of four bivariate statistical models that are commonly used in research: ANOVA, proportions, regression, and logistic. The text teaches statistical inference principles using resampling methods (such as randomization and bootstrapping), covering methods for hypothesis testing and parameter estimation. These methods are applied to each statistical model introduced in preceding chapters.


Data analytic examples are used to teach statistical concepts throughout, and students are introduced to the R packages and functions required for basic data analysis in each of the four models. The text also includes introductory guidance to the fundamentals of data wrangling, as well as examples of write-ups so that students can learn how to communicate findings. Each chapter includes problems forpractice or assessment. Supplemental instructional videos are also available as an additional aid to instructors, or as a general resource to students. 

This book is intended for an introductory or basic statistics course with an applied focus, or an introductory analytics course, at the undergraduate level in a two-year or four-year institution. This can be used for students with a variety of disciplinary backgrounds, from business, to the social sciences, to medicine. No sophisticated mathematical background is required.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

Bruce Blaine is Senior Lecturer in the Statistics Program at the University of Rochester. He is also an accredited Professional Statistician (PStat) through the American Statistical Association. Dr. Blaine's research interests include quantitative methods in the social sciences, meta-analysis, robust and nonparametric statistical methods, and R computing in data analysis.

Dalla quarta di copertina

This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods. It covers robust and non-robust descriptive statistics used in each of four bivariate statistical models that are commonly used in research: ANOVA, proportions, regression, and logistic. The text teaches statistical inference principles using resampling methods (such as randomization and bootstrapping), covering methods for hypothesis testing and parameter estimation. These methods are applied to each statistical model introduced in preceding chapters.


Data analytic examples are used to teach statistical concepts throughout, and students are introduced to the R packages and functions required for basic data analysis in each of the four models. The text also includes introductory guidance to the fundamentals of data wrangling, as well as examples of write-ups so that students can learn how to communicate findings. Each chapter includes problems forpractice or assessment. Supplemental instructional videos are also available as an additional aid to instructors, or as a general resource to students. 

This book is intended for an introductory or basic statistics course with an applied focus, or an introductory analytics course, at the undergraduate level in a two-year or four-year institution. This can be used for students with a variety of disciplinary backgrounds, from business, to the social sciences, to medicine. No sophisticated mathematical background is required.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Altre edizioni note dello stesso titolo

9783031277429: Introductory Applied Statistics: With Resampling Methods & R

Edizione in evidenza

ISBN 10:  3031277422 ISBN 13:  9783031277429
Casa editrice: Springer, 2023
Brossura