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This is an introductory applied statistics text that can be used for a one- or two-semester course at either the undergraduate or graduate level. Central features are its hands-on approach; the use of real data; the wealth of exercises and illustrated examples using these data; the complete set of detailed answers to exercises in an appendix; the presentation of statistical methods with a clear, conceptual emphasis that includes an historical account of each method; and the integration of SPSS in a way that reflects statistical practice. Step-by-step instructions for using SPSS are provided as each new analytic procedure is introduced. A data CD is included with the text so that students may conduct their own statistical analyses and learn firsthand how statistics is used in practice.
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"This first edition of Statistics Using R: An Integrative Approach capitalizes on the versatility and power of the R software package to create a course of study that links good statistical and data science practice to the analysis of real data. It also benefits from the many years of the authors' experience teaching statistics to undergraduate students at a liberal arts university and to undergraduate and graduate students at a large research university from a variety of disciplines including education, psychology, health, and policy analysis. Because R, a free, open-source software, provides a command line approach to the analysis of data, and, in so doing, this textbook teaches readers the skills necessary to program statistical analyses"--
R (Computer program language) --- Mathematical statistics --- Statistics --- #SBIB:303H510 --- #SBIB:303H4 --- #SBIB:303H61 --- GNU-S (Computer program language) --- Domain-specific programming languages --- Data processing --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Informatica in de sociale wetenschappen --- Wiskundige methoden en technieken --- Programming --- R (Computer program language). --- Data processing.
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“Statistics Using R introduces the most up-to-date approaches to R programming alongside an introduction to applied statistics using real data in the behavioral, social, and health sciences. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes an online R tutorial for learning the basics of R, as well as two R files for each chapter, one in Base R code and the other in tidyverse R code, that were used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important take-aways of each chapter. This textbook is appropriate for both undergraduate and graduate students in social sciences, applied statistics, and research methods. Offers a conceptual approach to topics in data science and analysis, grounded in examples using real data ; Integrates the popular and free R statistical computing software, providing easily editable R files for each chapter ; Links good statistical and data science practice to the analysis of real data in the behavioral, social, and health sciences”
R (Computer program language) --- Mathematical statistics --- Statistics --- Statistique mathématique --- Statistique --- Data processing. --- Data processing. --- Informatique. --- Informatique. --- R
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