Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods. Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes com…
Statistics Using R will be useful at different levels, from an undergraduate course in statistics, through graduate courses in biological sciences. engineering, management and so on. The book introduces statistical terminology and defines it for the benefit of a novice. For a practicing statistician, it will serve as a guide to R language for statis…
This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessi…
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R's syntax, you will work through data …
This book is all about the different statistical methods employed in the field of applied biology. Essentially these statistical methods and techniques were developed in the medical and biological sciences. However, these are also widely used in the social sciences as well as in the field of engineering and technology. The primary goal in scientific…
Covering the technical and professional skills needed by analysts in the academic, private, and public sectors, Applying Analytics: A Practical Introduction systematically teaches you how to apply algorithms to real data and how to recognize potential pitfalls.
The text concentrates on the interpretation, strengths, and weaknesses of analytical t…