*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.

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 ...

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

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 ...

The module will introduce students to basic concepts and techniques such as hypothesis testing and confidence interval estimation in statistics. Students will learn some simple statistical methods and ...

MR. UDNY YULE'S “Introduction” was the first book on statistics that came into my hands. This was about 1916. I liked it then and learned a lot from it. I like it even more now in its eleventh edition ...

Basic statistical concepts presented with emphasis on their relevance to biological and medical investigations. Evaluation is through problem sets, quizzes embedded within asynchronous videos, use of ...

Whatever study you choose to conduct, it will probably have a target population. The target population is the group of people who could be involved in your study. For example, if you wanted to do some ...