Housed in the Department of Applied Mathematics, the Laboratory for Interdisciplinary Statistical Analysis (LISA) trains students to become effective interdisciplinary collaborators who can apply ...

R is a free computing and graphical software/environment for statistical analysis. This short course is designed to provide a basic statistical analysis in R using two data. The first data set comes ...

In today's data-driven world, statistical analysis plays a critical role in uncovering insights, validating hypotheses, and driving decision-making across industries. R, a powerful programming ...

Our laboratory has developed a range of data analysis workflows that incorporate advanced statistical and computational methods to interpret the complex molecular datasets generated by MS technologies ...

Students are generally excited to learn hands-on field methods. However, the nuanced logistics required to curate collaborative datasets are considered more tedious; and many students find data ...

When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...

The 'big data' era sees every person generating a deluge of high-dimensional data, from clicks and purchases to sensor readings and survey responses. Yet the complexity of this data is often driven by ...

A statistical analysis of the distribution of returns can be used to determine many key characteristics of a stock's behavior. Volatility is not the only useful measure of risk that can be determined ...