Collecting data; summarizing and displaying data; drawing conclusions and making decisions using data; probability background, confidence intervals, hypotheses tests, regression, correlation. Not open ...

The purpose of the course is to introduce the statistical methods that are critical in the performance analysis and selection of information systems and networks. It includes fundamental topics as ...

Understanding some statistics is important for general science literacy. Below are some common statistics resources that may be useful for your project work. To support your professional development, ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

The field of statistics is a fundamental cornerstone of clinical and public health research, playing a key role in improving scientific understanding and developing successful health policy. This ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

This course introduces students to statistics and quantitative information. The course surveys probability theory, hypothesis testing, descriptive statistics and visualizations, and inferential ...

Contents: The R programming language is used for statistical data analysis and visualization. R and the R Studio development environment are a globally used tool set for statistical analysis and data ...

An introduction to probability theory and statistical methods especially as they relate to public policy. The course will consist of a brief introduction to probability theory as well as various ...