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 ...

Introduction to statistical methods applied to analysis of engineering systems. Topics include data collection, distribution characteristics, probability, uses of regression analysis, and ...

This course is a self-contained introduction to probabilistic and statistical methods used in risk management. A number of important questions and methods will be examined, including: How is the risk ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

Various statistical forecasting methods exist designed for use with slow-moving products, new product introductions, stable mature products and products with erratic demand. Determining which ...

Description: Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, ...

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 ...

Outliers may provide useful information about the development and manufacturing process. Analysts use various statistical methods to evaluate outliers and to reduce their impact on the analysis. This ...