#  Degree Tracks 

 



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The concentration requirements can be fulfilled via any of the four tracks:



 

 Stats Principles/Methods Data Science ML BCB 

## Stats Principles/Methods

 

 

   ![statistics](/sites/g/files/omnuum10116/files/styles/hwp_1_1__360x360_scale/public/statistics-2/files/statistics.png?itok=YCy1qJd5) 

 

The **general track** is the most flexible track, providing a foundation in principles and techniques for statistical theory, methods, and applications. This foundation can be applied to a myriad of fields. As John Tukey said, "The best thing about being a statistician is that you get to play in everybody else's backyard."

 



 

 

 

## Data Science

 

 

   ![Dats Science](/sites/g/files/omnuum10116/files/styles/hwp_1_1__360x360_scale/public/statistics-2/files/data-science.png?itok=dBAXX15W) 

 

The **data science track** explores the interface of statistics and computer science. Courses involve a mixture of these fields, with applications to areas such as prediction, recommendation systems, and analysis of massive data sets.

 



 

 

 

## ML

 

 

   ![finance](/sites/g/files/omnuum10116/files/styles/hwp_1_1__360x360_scale/public/statistics-2/files/finance.png?itok=WASH9PEf) 

 

The **Machine Learning track**  focuses on statistical and computational algorithms for tasks such as using data (possibly high-dimensional) to make predictions and decisions under uncertainty, and for classification and clustering. Topics in statistical machine learning such as supervised learning, unsupervised learning, and reinforcement learning are emphasized. 

 



 

 

 

## BCB

 

 

   ![Bio](/sites/g/files/omnuum10116/files/styles/hwp_1_1__360x360_scale/public/statistics-2/files/bio.png?itok=5gUl77ir) 

 

The **Bioinformatics and Computational Biology (BCB) track** mixes together biology, statistics, and computation, giving models and tools for studying biological data such as gene and protein sequences. This is motivated in part by the recent explosion of size and complexity of data in the biological sciences, which has required the development of new statistical methods and models, such as models for gene and protein motifs search, phylogenetic reconstruction, and gene expression analysis.