Data Visualization

What Are Vowels Made Of? Graphing a Classic Dataset with R

February 13, 2024
by Anna Björklund. Vowels are all around us. Mainstream US English has around twelve unique vowels. How can our brains tell these sounds apart? This blog post will help you answer this question by plotting vowel data from a classic American English dataset by Peterson and Barney (1952).

Jailynne Estevez

Consulting Drop-In Hours: Fri 3pm-5pm

Consulting Areas: Python, SQL, Stata, HTML / CSS, Javascript, Google AppScripts, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Python Programming, Surveys, Sampling & Interviews, Text Analysis, , Bash or Command Line, Excel, Git or Github, Stata

Quick-tip: the fastest way to speak to a consultant is to first ...

Anna Björklund

Data Science Fellow
Linguistics

I am a fifth-year PhD student in the Department of Linguistics with an areal interest in the Wintuan languages, traditionally spoken in the northern Sacramento Valley and now undergoing revitalization. My primary research interests are in leveraging archival recordings for the phonetic analysis of these under-documented languages, as well as designing tools to assist in their revitalization. I have worked as a linguistic consultant for the Paskenta Band of Nomlaki Indians since 2020 and the Wintu Tribe of Northern California since 2022. I received my MA in linguistics from UC...

Chirag Manghani

Consulting Drop-In Hours: Wed 1pm-3pm

Consulting Areas: Python, R, SQL, Stata, SAS, LaTeX, HTML / CSS, Javascript, C++, APIs, Cloud & HPC Computing, Cybersecurity & Data Security, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Deep Learning, Machine Learning, Natural Language Processing, Python Programming, R Programming, Software Tools, Text Analysis, Web Scraping, Regression Analysis, Software Output Interpretation, Bash or Command Line, Excel, Git or Github, Qualtrics, RStudio, RStudio...

Nicolas Nunez-Sahr

Consulting Drop-In Hours: By appointment only

Consulting Areas: Python, R, SQL, C++, APIs, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Visualization, Deep Learning, Machine Learning, Natural Language Processing, Python Programming, R Programming, Text Analysis, Regression Analysis, Software Output Interpretation, Bash or Command Line, Git or Github, RStudio, Google Cloud, PostgreSQL, Python Django

Quick-tip: the fastest way to speak to a consultant is to first ...

Lauren Chambers

Consulting Drop-In Hours: Wed 11am-1pm

Consulting Areas: Python, R, HTML / CSS, APIs, Data Manipulation and Cleaning, Data Science, Data Visualization, Python Programming, R Programming, Software Tools, Web Scraping, Regression Analysis, Software Output Interpretation, Bash or Command Line, Git or Github, OCR, RStudio

Quick-tip: the fastest way to speak to a consultant is to first ...

Jane Angar

Consulting Drop-In Hours: Wed 9am-11am

Consulting Areas: R, Stata, LaTeX, Data Manipulation and Cleaning, Data Visualization, Qualitative methods, R Programming, Regression Analysis, Means Tests, Excel, Git or Github, Qualtrics, RStudio, Stata, Jupiter Notebook

Quick-tip: the fastest way to speak to a consultant is to first ...

Creating the Ultimate Sweet

January 30, 2024
by Emma Turtelboom. What is the best Halloween candy? In this blog post, we will identify attributes of popular sweets and create a model to understand how these attributes influence the popularity of the sweet. We’ll discuss alternative model approaches and potential drawbacks, as well as caveats to interpreting the predictions of our model.

Addison Pickrell

IUSE Undergraduate Advisory Board
Mathematics
Sociology

Addison is an aspiring mathematician and social scientist (Class of '27). He loves collecting books he'll never read, is an open-source and open-access advocate, and an aspiring community organizer and systems disrupter. Ask me about community-based participatory action research (CBPAR), critical pedagogy, applied mathematics, and social science.

Tracking Urban Expansion Through Satellite Imagery

December 12, 2023
by Leïla Njee Bugha. Among its many uses, remote sensing can prove especially useful to document changes and trends from eras or settings, where traditional sources are either inexistent or infrequently collected. This is the case when one wants to study urban expansion in sub-Saharan countries over the past 20 years. To further remedy the lack of data on land cover uses from earlier time periods, classification methods can be used as well. Using easily accessible satellite imagery from Google Earth Engine, I provide here an example combining remote sensing with classification to detect changes in the land cover in Nigeria since 2000 due to urban expansion.