Data Visualization

Gaby May Lagunes

Consultant
ESPM

Hello! I’m Gaby (she/her). I am PhD student at the ESPM department, I hold a masters in Data Science and Information from the Berkeley ISchool and I have 5+ years of industrial experience in different data roles. Before that I got a masters in Engineering for International Development and an undergraduate degree in Physics from University College London. And somewhere between all that I got married, survived the pandemic, and had two awesome boys. I’m very excited to help you use data to enhance your work and your experience here at Berkeley!

Thomas Lai

Consultant
School of Information

I am a Product Engineer passionate about applying engineering, data science, machine learning, and problem-solving principles to improve device performance and solve complex challenges. With experience in statistical analysis, lab bench automation, and Python scripting, I have developed a strong technical skill set that allows me to make meaningful contributions to any project. Beyond my work, I am also passionate about exploring new topics and ideas, from the latest technology trends to how to improve the overall well-being of humans. I enjoy applying the first principle to any...

Design Your Observational Study with the Joint Variable Importance Plot

March 12, 2024
by Lauren Liao. When evaluating causal inference in observational studies, there often is a natural imbalance in the data. Luckily, variables are often measured alongside that can be helpful for adjustment. However, deciding which variables should be prioritized for adjustment is not trivial – since not all variables are equally important to the intervention or the outcome. I recommend using the joint variable importance plot during the observational study design phase to visualize which variables should be prioritized. This post provides a gentle guide on how to do so and why it is important.

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).

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.

Exploratory Data Analysis in Social Science Research

November 14, 2023
by Kamya Yadav. Causal inference has become the dominant endeavor for many political scientists, often at the expense of good research questions and theory building. Returning to descriptive inference – the process of describing the world as it exists – can help formulate research questions worth asking and theory that is grounded in reality. Exploratory data analysis is one method of conducting descriptive inference. It can help social science researchers find empirical patterns and puzzles that motivate their research questions, test correlations between variables, and engage with the existing literature on a topic. In this blog post, I walk through results from exploratory data analysis I conducted for my dissertation project on political ambition of women.

Mapping Census Data with tidycensus

November 6, 2023
by Alex Ramiller. The U.S. Census Bureau provides a rich source of publicly available data for a wide variety of research applications. However, the traditional process of downloading these data from the census website is slow, cumbersome, and inefficient. The R package “tidycensus” provides researchers with a tool to overcome these challenges, enabling a streamlined process to quickly downloading numerous datasets directly from the census API (Application Programming Interface). This blog post provides a basic workflow for the use of the tidycensus package, from installing the package and identifying variables to efficiently downloading and mapping census data.

Introduction to Item Response Theory

October 24, 2023
by Mingfeng Xue. Measurements (e.g., tests, surveys, questionnaires) are inevitably involved with various sources of errors. Among many psychometric theories, item response theory stands out for its capability of detailed analyses at the item level and its potential to reduce some of the measurement errors. This post first discussed the limitations of conventional summation and average, which give rise to the IRT models, and then introduced a basic form of the Rasch model, including expressions of the model, the assumptions underlying it, some of its advantages, and software packages. Some codes are also provided.