UC Davis Department of Statistics

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Recent developments in statistics, data mining, machine learning and other related fields have been motivated by the need to make sense of increasingly large and complex data that are generated across the sciences, medicine, business and society, and the “Big Data” challenge with billions of terabytes of data being generated." /> <link rel="canonical" href="https://statistics.ucdavis.edu/mission" /> <meta property="og:site_name" content="UC Davis Department of Statistics" /> <meta property="og:type" content="website" /> <meta property="og:url" content="https://statistics.ucdavis.edu/mission" /> <meta property="og:title" content="Mission" /> <meta property="og:description" content="Statistics is a Data Science that provides theory, methods and computational tools for inference, prediction and data analysis. Recent developments in statistics, data mining, machine learning and other related fields have been motivated by the need to make sense of increasingly large and complex data that are generated across the sciences, medicine, business and society, and the “Big Data” challenge with billions of terabytes of data being generated." /> <meta property="og:image:width" content="1280" /> <meta property="og:image:height" content="720" /> <meta property="og:updated_time" content="2016-07-05T14:02:16-07:00" /> <meta property="article:author" content="Site Factory admin" /> <meta property="article:published_time" content="2013-09-09T14:31:26-07:00" /> <meta property="article:modified_time" content="2016-07-05T14:02:16-07:00" /> <meta name="Generator" content="Drupal 10 (https://www.drupal.org)" /> <meta name="MobileOptimized" content="width" /> <meta name="HandheldFriendly" content="true" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <meta http-equiv="X-UA-Compatible" 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The Department of Statistics hosts more than 400 undergraduate statistics majors and houses graduate programs in Statistics and Biostatistics.</p> <p>The mission of the Department of Statistics includes as core elements:</p> <ul> <li>Training of undergraduate students, aiming to provide students with: a broad education in statistics, emphasizing key concepts; basic technical skills; an appreciation for good statistical practice; the ability for critical statistical reasoning; opportunities to participate in research; preparation for graduate school and for professional careers.</li> <li>Training of graduate students through the Graduate Program in Statistics, aiming to educate and train statisticians that are firmly grounded in statistical methodology, computing and theory and are well prepared and qualified to solve complex data analysis problems and to address the current data challenges. MS students gain a solid understanding of fundamental statistical concepts and methodology, as well as well-honed data handling and data analysis skills, and thus are well prepared for professional careers as statisticians. PhD students graduating from our program are well prepared to carry out research that leads to fundamental contributions to the field of Statistics and its applications, and to carry out collaborative research with domain scientists. Involvement in independent and collaborative research prepares the PhD students for advanced positions in academia, industry and government.</li> <li>Participation of faculty and graduate students at the forefront of current research, including the development of new theory, methodology, algorithms and applications. Of specific interest are contributions to a deeper understanding of the methodologies developed for the analysis of modern data sets; the exploration of commonalities of related challenges; and the discovery of hidden unifying structures. Such higher-level understanding allows for the synthesis of methodologies and technologies with the potential of borrowing strength across methods.</li> <li>Collaboration of faculty and graduate students with investigators who collect or curate data. Such collaboration often will: require advanced data analysis for large and complex data; motivate the creation of new statistical methodology; and showcase the value of statistical analysis. 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