Statistics

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.

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.

by Renee Starowicz. Renee Starowicz, Co-Executive Director of the Berkeley Federal Statistical Research Data Center, provides an overview of the takeaways from the 2023 Annual Federal Statistical Research Data Center Business Meeting and Annual Conference. She provides a brief overview of the Berkeley FSRDC. Then, she describes the priorities for collaboration across national directors to improve outreach to diverse researchers and transparency. Additionally, she points out the other key topics of conversation at this year’s meeting.

by Leena Bhai. This blog post provides an introduction to field experimentation and its significance in understanding cause and effect. It explains how randomized experiments represent an unbiased method for determining what works. It delves into essential features of experiments such as intervention, excludability, and non-interference. It then works through a fictional example of a randomized controlled trial of the efficacy of an experimental drug Covi-Mapp.