StatLab: Data Analytics

We offer consultations, collaborations, and training in support of data science, applied statistics, and scientific computing, including data wrangling and cleaning, analysis and visualization, statistical inference and computational methods, reproducibility and open science.

Staff expertise also encompasses open source programming languages like R and Python; statistical environments like Stata, SPSS, SAS; scientific computing technologies like Unix, Github, and Overleaf; visualization software  (Tableau), and software for qualitative data (Dedoose). We can help with data collection via web scraping and APIs in R and Python and working with structured and unstructured (e.g., text) data. Plus,

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