TY  - BOOK
AU  - Mehmetoglu,Mehmet
AU  - Mittner,Matthias
TI  - Applied statistics using R : : a guide for the social sciences 
SN  - 9781526476227
AV  - H61.3 .M44 2022
U1  - 300.285/5133 23
PY  - 2022///]
CY  - London, Thousand Oaks, Calfornia
PB  - SAGE Publications Ltd
KW  - Social sciences
KW  - Research
KW  - Data processing
KW  - Statistical methods
KW  - R (Computer program language)
KW  - Sciences sociales
KW  - Recherche
KW  - Informatique
KW  - Méthodes statistiques
KW  - R (Langage de programmation)
KW  - fast
N1  - Includes bibliographical references (pages 437-442) and index; Chapter 1: Introduction to R - Chapter 2: Importing and working with data in R - Chapter 3: How does R work? - Chapter 4: Data management - Chapter 5: Data visualisation with ggplot2 - Chapter 6: Descriptive statistics - Chapter 7: Simple (bivariate) regression - Chapter 8: Multiple linear regression - Chapter 9: Dummy-variable regression - Chapter 10: Moderation/interaction analysis using regression    Chapter 11: Logistic regression - Chapter 12: Multilevel and longitudinal analysis - Chapter 13: Factor analysis - Chapter 14: Structural equation modelling - Chapter 15: Bayesian statistics
N2  - If you want to learn to use R for data analysis but aren’t sure how to get started, this practical book will help you find the right path through your data.

Drawing on real-world data to show you how to use different techniques in practice, it helps you progress your programming and statistics knowledge so you can apply the most appropriate tools in your research.

It starts with descriptive statistics and moves through regression to advanced techniques such as structural equation modelling and Bayesian statistics, all with digestible mathematical detail for beginner researchers.

The book:

Shows you how to use R packages and apply functions, adjusting them to suit different datasets.
Gives you the tools to try new statistical techniques and empowers you to become confident using them.
Encourages you to learn by doing when running and adapting the authors’ own code.
Equips you with solutions to overcome the potential challenges of working with real data that may be messy or imperfect.
Accompanied by online resources including screencast tutorials of R that give you step by step guidance and R scripts and datasets for you to practice with, this book is a perfect companion for any student of applied statistics or quantitative research methods courses
ER  -