## Programs by Campus

### Bloomington

#### Statistics

###### College of Arts and Science

**Departmental E-mail**: statdept [at] indiana [dot] edu

**Departmental URL**: www.stat.indiana.edu/

(Please note that when conferring University Graduate School degrees, minors, certificates, and sub-plans, The University Graduate School’s staff use those requirements contained only in *The University Graduate School Bulletin.*)

###### Curriculum

###### Degrees Offered

- Master of Science in Applied Statistics
- Master of Science in Statistical Science
- Doctor of Philosophy in Statistical Science

###### Special Departmental Requirements

(See also general University Graduate School requirements.)

**Admission Requirements**

Statistics is an increasingly interdisciplinary field. Recognizing that fact, the IU Department of Statistics welcomes students from a variety of quantitative backgrounds, not just statistics and mathematics.

To be admitted to the Master of Science in Applied Statistics program a student must be pursuing a Ph.D. in another program at IU.

Students entering our Master of Science or Ph.D. in Statistical Science programs should have a bachelor's or master's degree from an accredited university. Academic preparation should include at least two undergraduate courses in statistics, some background in mathematics that includes courses in multivariate calculus and linear algebra, and some familiarity with computer programming.

Applicants will be evaluated using a combination of academic transcripts, grade-point averages, GRE scores, TOEFL scores (for international applicants), letters of recommendation, and personal statements. Selection criteria include breadth and depth of preparation, quality of academic performance, and motivation.

**Master of Science in Applied Statistics**

The M.S. in Applied Statistics is intended for the student pursuing a Ph.D. degree in another field who wishes to enhance his or her statistical knowledge and credentials by obtaining a graduate degree in Statistics, in addition to a Ph.D. degree in his or her primary field of study.

**Course Requirements**

A total of 31 credit hours, 19 of which must be in the Department of Statistics and include the following courses: (1) STAT S520 or S620; (2) one of S610, S611, S612; (3) S631, S632, and S690. The remaining 12 credit hours must be taken in an area relevant to the field of Statistics, and must be approved by the Director of Graduate Studies.

MSAS students who will have a statistical sciences minor will complete the minor coursework prior to submitting their candidacy and may use all the statistical sciences minor coursework towards the MSAS. This could be either three courses in stats plus one course (12 credits total) from the major department (but not a required core course within the major) OR could be four courses from within stats. The student then will be permitted to use an additional three courses (9 credits total) from the PhD courses towards the MSAS requirements. In this case, total number of courses allowed to be used from the MSAS towards the PhD is four (12 credits), the total courses allowed from the PhD towards the MSAS is seven (21 credits). The student would need three additional courses that are not used in the PhD to complete the MSAS requirements.

MSAS students who do not have a statistical sciences minor can use no more than 12 credit hours from the PhD towards the MSAS (in the PhD major and/or minor courses).

**Master of Science in Statistical Science**

The M.S. program trains students to become applied statisticians who collaborate with researchers in various disciplines to design experiments and analyze data.

**Course Requirements **

A total of 31 credit hours including MATH M463, STAT S610, S611, S620, S631, S632, and S690. Students must also complete either a one-semester consulting internship, S692, or a thesis, S799. The remaining 6 credit hours can be from any graduate statistics courses approved by the Director of Graduate Studies.

**Doctor of Philosophy in Statistical Science**

The Ph.D. program trains students as research statisticians who develop new statistical methodology. This program is for graduate students who wish to obtain positions as research statisticians in academia, government, or industry.

**Course Requirements**

A total of 90 credit hours, including at least 60 credit hours of coursework; dissertation research to reach 90 credit hours.

Core Courses (9 credit hours): Math-M 413: Introduction to Analysis I, STAT-S 620: Introduction to Statistical Theory, STAT-S 611: Applied Statistical Computing

Data Analysis Courses (12 credit hours): STAT-S 631: Applied Linear Models I, STAT-S 632: Applied Linear Models II, STAT-S 771: Advanced Data Analysis I, STAT-S 772: Advanced Data Analysis II

Advanced Statistical Theory Courses (12 credit hours): STAT-S 721: Advanced Statistical Theory I, STAT-S 722: Advanced Statistical Theory II plus at least two semesters of STAT-S 785: Seminar on Statistical Theory

Elective and Minor Courses (27 credit hours): All students must complete a Ph.D. minor in another graduate program. Minor requirements are specified by the awarding department and are described in the University Graduate School Bulletin. All courses in this category must be approved by the Director of Graduate Studies.

**Qualifying Examination**

Students advance to candidacy by completing required coursework and passing two qualifying examinations. The Statistical Theory exam is a written examination based on material covered in STAT-S 721-722 (Advanced Statistical Theory). This exam is usually administered in May, after the 722 semester concludes. The Data Analysis exam consists of an oral presentation and a paper based on a project completed in STAT-S 771-772 (Advanced Data Analysis). The oral presentation usually takes place near the end of the 772 semester and the paper then incorporates suggested revisions. Students who fail either qualifying examination more than once will be dismissed from the program.

**Advisory and Research Committees**

For each student admitted to the PhD program, a doctoral advisory committee will be formed in the first year of training. After passing their qualifying exams, students must form a research (dissertation) committee. The student’s committee (advisory or research) will consult with the student at least once per year to help the student determine his/her course of graduate study, develop a research program, approve the student’s course selections, and review the student’s progress in all areas (for example, completion of required courses, course grades, and research progress). The student’s committee will determine whether or not the student is making adequate progress in all areas. Should the advisory (or research) committee determine that a student is not making adequate progress in any area, this may be grounds for eliminating a student’s department funding, probation, or dismissal from the program.

**Dissertation Proposal and Research**

A dissertation is required. The dissertation represents original methodological research by the student. The research should be of sufficient quality to merit publication in peer-reviewed journals.

After passing the qualifying exams, students should begin the process of finding a dissertation advisor, forming a dissertation committee, and identifying a dissertation topic. The dissertation proposal is an oral exam intended to demonstrate to the statistics faculty that the student is prepared to begin research. The student will make an oral presentation that outlines the proposed research, including summaries of related work and descriptions of the techniques that will be used. The dissertation committee and other statistics faculty will then question the student.

**Ph.D. Minor in Statistical Science**

Doctoral students obtaining a Ph.D. in another discipline are welcome to choose Statistics as an outside minor. Four graduate courses in statistics are required, at least three of which must be at the 600-level or above taken from the Department of Statistics. The specific minor courses must be approved by the Director of Graduate Studies of the Department of Statistics.