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 ...

This is an introductory course in statistics. Topics that we will cover include elementary statistical measures, statistical distributions, statistical inference, hypothesis testing and linear ...

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 ...

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

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 ...

This is an introductory course on statistics and how it can help us answer the kind of questions that arise when we want to better understand the world. We will use real-world examples from the social ...

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 ...