Visualization

R Data Visualization

March 29, 2023, 2:00pm
This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures.

R Visualization

February 10, 2022, 5:00pm
This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures.

Python Fundamentals: Parts 1-3

August 14, 2023, 2:00pm
This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Qualtrics Fundamentals

March 29, 2022, 3:00pm
Qualtrics is a powerful online tool available to Berkeley community members that can be used for a range of data collection activities. Primarily, Qualtrics is designed to make web surveys easy to write, test, and implement, but the software can be used for data entry, training, quality control, evaluation, market research, pre/post-event feedback, and other uses with some creativity.

Propensity Score Matching for Causal Inference: Creating Data Visualizations to Assess Covariate Balance in R

June 10, 2024
by Sharon Green. Although some people consider randomized experiments the gold standard, in many cases, it would be highly unethical to assign individuals to harmful exposures to measure their effects. Modern causal inference techniques help scientists to estimate treatment effects using observational data. In particular, propensity score matching helps scientists estimate causal effects using observational data by matching individuals so that the “treatment” and “control” groups are balanced on measured covariates. After implementing propensity score matching, data visualizations make it easier to assess the quality of the matches before estimating effects. This blog post is a tutorial for implementing propensity score matching and creating data visualizations to assess covariate balance–that is, visually assessing whether the matched individuals are balanced with respect to measured covariates.

Stata for Research Transparency and Reproducibility Training (RT2)

June 7, 2024, 3:15pm
This is a custom Stata workshop for the 2024 Research Transparency and Reproducibility Training (RT2).

Tactics for Text Mining non-Roman Scripts

April 15, 2024
by Hilary Faxon, Ph.D. & Win Moe. Non-Roman scripts pose particular challenges for text mining. Here, we reflect on a project that used text mining alongside qualitative coding to understand the politicization of online content following Myanmar’s 2021 military coup.

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.

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.