211 citations · 228 across the 7 of their papers we have counts for
7 papers
Measuring the Impact of Missingness in Traffic Stop Data
Saatvik Kher, Johanna Hardin
In this article we explore the data available through the Stanford Open Policing Project. The data consist of information on millions of traffic stops across close to 100 different…
A Mathematical Lens for Teaching Data Science
Johanna Hardin
Using the National Academies report, {\em Data Science for Undergraduates: Opportunities and Options}, we connect data science curricula to the more familiar pedagogy used by many…
Exploring Exchangeability within Permutation Inference: Implications for Statistics and Data Science Educators
Johanna Hardin, Lauren Quesada, Julie Ye +1
Permutation tests are a powerful and flexible approach to inference via resampling. As computational methods become more ubiquitous in the statistics curriculum, use of permutation…
Prediction Error Estimation in Random Forests
Ian Krupkin, Johanna Hardin
In this paper, error estimates of classification Random Forests are quantitatively assessed. Based on the initial theoretical framework built by Bates et al. (2023), the true error…
Community, Collaboration, and Climate
Johanna Hardin, Shahriar Shahriari
The Department of Mathematics & Statistics at Pomona College has long worked to create an inclusive and welcoming space for all individuals to study mathematics. Many years ago, ou…
An educator's perspective of the tidyverse
Mine Çetinkaya-Rundel, Johanna Hardin, Benjamin S. Baumer +3
Computing makes up a large and growing component of data science and statistics courses. Many of those courses, especially when taught by faculty who are statisticians by training,…
Data Science in Statistics Curricula: Preparing Students to "Think with Data"
Johanna Hardin, Roger Hoerl, Nicholas J. Horton +1
A growing number of students are completing undergraduate degrees in statistics and entering the workforce as data analysts. In these positions, they are expected to understand how…