Engelska

Cooksafe [Bok / Inbunden]

Understanding and Using Advanced Statistics is a comprehensive, practical guide for postgraduate students advising how and when to use more advanced statistical methods. Perfect for students without a mathematical background, the authors refresh important basics such as descriptive statistics and research design as well as introducing essential upper-level techniques to cater for the advanced student. Key Features:- Comprehensive guide informing how to use a range of advanced statistical methods such as MANOVA, path analysis and logistical regression;- Inter-disciplinary: ideal for students studying upper level statistical methods in any subject across the social sciences;- Practical guide: case studies, further reading, key terms explained in order to help the non-mathematically orientated student get ahead with their research. Building on undergraduate statistical grounding, Understanding and Using Advanced Statistics provides the upper-level researcher with the knowledge of what advanced statistics do, how they should be used, and what their output means.

The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you:<br/><br/>- Data wrangling - importing, formatting, reshaping, merging, and filtering data in R.<br/><br/>- Exploratory data analysis - using visualisation and multivariate techniques to explore datasets.<br/><br/>- Statistical inference - modern methods for testing hypotheses and computing confidence intervals.<br/><br/>- Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting.<br/><br/>- Simulation - using simulation techniques for sample size computations and evaluations of statistical methods.<br/><br/>- Ethics in statistics - ethical issues and good statistical practice.<br/><br/>- R programming - writing code that is fast, readable, and free from bugs.<br/><br/>Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions.<br/><br/>Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.