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Wharton's Statistics and Data Science PhD program equips students with core training to tackle both advanced theoretical concepts and real-world applications. These span diverse disciplines at Wharton, including finance, marketing, and public policy, as well as other University departments like biostatistics in the Medical School and computer science in Engineering. Key research focuses encompass: observational study analysis, Bayesian methods, bioinformatics, decision and game theory, high-dimensional inference, information theory, machine learning, model selection, nonparametric estimation, and time series. Applicants generally possess robust mathematical preparation at the undergraduate level, with linear algebra and advanced calculus being essential, while real analysis experience is beneficial. While some prior coursework in probability and statistics is assumed, mathematical and computational abilities carry greater weight. Alumni commonly pursue careers in academia, government, finance, and biopharmaceutical sectors.
Students typically have a strong undergraduate background in mathematics. Knowledge of linear algebra and advanced calculus is required, and experience with real analysis is helpful. Although some exposure to undergraduate probability and statistics is expected, skills in mathematics and computer science are more important.
A strong command of the English language is necessary for successful study at Penn. Applicants whose families do not speak English at home, or applicants who have not attended a high school or secondary school where the primary language of instruction is English, are asked to take the TOEFL, the Test of English as a Foreign Language, administered by the Educational Testing Service. In the event the TOEFL is not readily accessible, Penn will accept results from the IELTS, the International English Language Testing System.