data relationships; correlation; inference with confidence; significance tests; network simulation and analysis; performance analysis of systems and networks. REQUIRED TEXT: Moore, McCabe & Craig, ...

data relationships; correlation; inference with confidence; significance tests; network simulation and analysis; performance analysis of systems and networks. REQUIRED TEXT: Moore, McCabe & Craig, ...

Leading research company Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025. If you’re new to graph and wondering what it can do for your ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

An introduction to descriptive statistics, graphing and data analysis, probability laws, discrete and continuous probability distributions, correlation and regression, inferential statistics. No ...

Introduction to Statistics in Human Performance: Using SPSS and R provides students facing statistical problems for the first time with an accessible and informal introduction to the key concepts and ...

However, in recent years the open source community has developed increasingly-sophisticated data manipulation, statistical analysis, and machine learning ... have a good understanding of the ...

Introduces students to the tools methods and theory behind extracting insights from data. Covers algorithms of cleaning and munging data, probability theory and common distributions, statistical ...

Applied statistics is data analysis. It’s managing, analyzing, interpreting, and drawing conclusions from data in order to make sound decisions in a wide range of fields, including engineering, ...

Several statistical methods have been proposed for modelling survival analysis data. We will describe the most important models and illustrate their application using example datasets described in ...