The Curious Case of Statistical Modeling in Social Sciences

by Miguel Escobar

The Curious Case of Statistical Modeling in Social Sciences The use of statistical models in the social sciences has a long and storied history. From the early work of Francis Galton and Karl Pearson to the more recent advances in machine learning, statistical modeling has played a vital role in helping us understand the world around us. However, the use of statistical models in the social sciences is also fraught with challenges. These challenges include The difficulty of defining and measuring social phenomena. Social phenomena are often complex and multifaceted, making it difficult to develop accurate and reliable measures. The problem of confounding variables. Confounding variables are factors that can influence the relationship between two variables of interest, making it difficult to isolate the effects of a particular variable. The problem of bias. Statistical models can be biased in a number of ways, including selection bias, measurement bias, and confounding bias. Despite these challenges, statistical modeling remains a valuable tool for social scientists.

496 pages, Kindle Edition

Published August 26, 2024