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Statistics and Biostatistics

Graduate Program

Assessment of Student Learning Outcomes

Our programs include an MS program and a PhD program.

MS Program

Program Description

Our MS program requires 30 credits in approved graduate courses; these credits are almost invariably earned through 10 three-credit courses. Coursework involves core courses in probability, statistical theory, experimental design, regression, and the interpretation of data. MS candidates are also required to pass a two-part comprehensive exam on statistical theory and practice, and to complete an MS essay.

Program Goals

Our MS graduates are expected to function as independent applied statisticians. These graduates should be prepared for careers in industry, government, the non-profit private sector, and in non-faculty academic positions. As such, they are expected to draw on traditional and newly-emerged statistical techniques, identify the appropriateness of a particular technique to a particular data context, apply the technique, either using hand calculation, or more commonly, using tested and verified standard statistical software, to appropriately interpret the results of such calculations, to report the results to practitioners knowledgeable in the field that generated the data, and to make minor extensions to these techniques.

Student Assessment

Candidates for admission to the MS program submit transcripts, letters of recommendation, and GRE scores. Transcripts are examined for evidence of mathematical competence through a second course in calculus and a course in linear algebra, and for evidence of statistical experience through a senior-level undergraduate methods course. Deficiencies in background are noted, and remediation of deficiencies is made a condition for admission.
A systematic set of prerequisites is enforced by the registrar, stopping students from registering for courses that they do not have the academic background for.
Students are allowed to count toward their degree no more than two courses with grades below B. Grades below B, and incomplete grades, are tracked by the secretary to the graduate director and called to the graduate director's attention. Students with more than one sub-B grade, or with more than one pending incomplete, are instructed to discuss the situation with the graduate director. Our MS program is designed to be completed part-time, and students completing less than 9 credits per year are also instructed to meet with the graduate director. Systematic tracking of degree candidates is performed via the GradPortal system.
Aside from course assessment, students are also assessed through the comprehensive exam, consisting of a theoretical and an applied section. Questions are set with the goal of assessing core competence in statistical application and theory, and the grading rubric is devised to calibrate passing with a confidence in the ability to function independently. Students are also required to complete an MS essay, demonstrating the ability to competently report the results of a complex statistical analysis.

Program Assessment

The faculty of Statistics and Biostatistics continuously reevaluates our graduate courses, to obtain courses with the following properties:

  • Core applied courses should contain the knowledge base currently required of all practicing applied statisticians.
  • Core theoretical courses should be the gateway for self study for mastery of techniques that become part of the standard statistical toolbox as the field of statistics develops.
  • Optional courses (including doctoral level courses accessible to our strongest MS students) should allow an introduction to emerging statistical techniques.

Exams are continuously assessed by examining the relationship between course grades and exam success, and the relationship between course and exam content.

PhD Program

Program Description

Our PhD program requires 48 credits in approved graduate courses; these credits are almost invariably earned through 16 three-credit courses. Coursework involves core courses in probability, statistical theory, and statistical methodology. PhD candidates are also required to pass a written exam on statistical theory, and an oral exam on advanced theory and statistical practice. Our PhD candidates must also write and defend a thesis consisting of original research.

Program Goals

We prepare our PhD graduates for careers as scholars. Central to their career is the pursuit of an ongoing research agenda. This research agenda is important, both for its own sake, and for its support of teaching and statistical practice. Students also receive direct preparation for teaching and statistical practice. PhD graduates engaged in statistical practice are prepared for analyses of data of nonstandard sources and structures, and are expected to develop and implement new statistical techniques. These graduates can also be expected to take leadership roles in their organizations.

Student Assessment

Candidates for admission to the PhD program submit transcripts, letters of recommendation, and GRE scores. Transcripts are examined for evidence of mathematical competence through real analysis, and for evidence of statistical experience through a senior-level undergraduate methods course. Deficiencies in background are noted, and remediation of deficiencies is made a condition for admission.
A systematic set of prerequisites is enforced by the registrar, stopping students from registering for courses that they do not have the academic background for.
Grades below B, and incomplete grades, are tracked by the secretary to the graduate director and called to the graduate director's attention. Students with more than one sub-B grade, or with more than one pending incomplete, are instructed to discuss the situation with the graduate director. Systematic tracking of degree candidates is performed via the GradPortal system.
Aside from course assessment, students are also assessed through the written and oral exams. Questions are set with the goal of assessing core competence in statistical theory, and the grading rubric is devised to calibrate passing with a confidence in the ability to successfully complete a thesis. Students are also required to complete a dissertation demonstrating the ability to perform original research.

Program Assessment

The faculty of Statistics and Biostatistics continuously reevaluates our graduate courses, to obtain courses with the following properties:

  • Core theoretical courses should give PhD students an understanding of traditional statistical principles, an understanding of the range of problems conventionally included in the discipline of statistics, an understanding of the various conventional solutions to these problems, and the vocabulary necessary to communicate the ideas involved in these problems and solutions. This body of knowledge is meant as a point of departure for the student's own thesis work, and not as a constraint on the scope of this work.
  • Optional courses should allow an introduction to emerging statistical areas.
  • Courses in applied methodology, often taken with MS students, should provide a background in contemporary statistical practice, with the aims of preparation for that portion of a career devoted to applications, and of exposure to possible research areas.
  • Courses in statistical computing should prepare students for the implementation of emerging statistical techniques.

Exams are continuously assessed by examining the relationship between course grades and exam success, and the relationship between course and exam content.

 

 

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General Inquiries: office@stat.rutgers.edu
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