000			02513nam a22002297a 4500
999			_c4138 _d4138
005			20221013143648.0
008			221013b ||||| |||| 00| 0 eng d
020			_a9781526486776
082			_a006.312 _bAND
100			_aAndrews, Mark _99338
245			_aDoing data science in R: _b an introduction for social scientists
260			_bSage Publications Ltd. _aLondon _c2021
300			_avi, 626 p.
365			_aGBP _b40.99
504			_aTable of content Chapter 1: Data Analysis And Data Science Chapter 2: Introduction To R Chapter 3: Data Wrangling Chapter 4: Data Visualization Chapter 5: Exploratory Data Analysis Chapter 6: Programming In R Chapter 7: Reproducible Data Analysis Chapter 8: Statistical Models and Statistical Inference Chapter 9: Normal Linear Models Chapter 10: Logistic Regression Chapter 11: Generalized Linear Models for Count Data Chapter 12: Multilevel Models Chapter 13: Nonlinear Regression Chapter 14: Structural Equation Modelling Chapter 15: High Performance Computing with R Chapter 16: Interactive Web Apps with Shiny Chapter 17: Probabilistic Modelling with Stan
520			_aThis approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and skills gradually. This book: Focuses on providing practical guidance for all aspects, helping readers get to grips with the tools, software, and statistical methods needed to provide the right type and level of analysis their data requires Explores the foundations of data science and breaks down the processes involved, focusing on the link between data science and practical social science skills Introduces R at the outset and includes extensive worked examples and R code every step of the way, ensuring students see the value of R and its connection to methods while providing hands-on practice in the software Provides examples and datasets from different disciplines and locations demonstrate the widespread relevance, possible applications, and impact of data science across the social sciences
650			_aR (Computer program language) _91512
650			_aBig data _9212
650			_aData mining _9365
650			_aSocial sciences--Research--Data processing _99659
942			_2ddc _cBK