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 describes basic statistical analysis in R using two data sets. The 1974 Motor Trend Car Road Tests ...

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 ...

Discover how proteomics data analysis and bioinformatics tools enhance mass spectrometry workflows for robust findings.

How to use statistical tools for component tolerance analysis. A look at methods such as Monte Carlo and Gaussian distribution. Simulating a dc-dc converter in LTspice to model closed-loop voltage ...