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University Bulletin
Graduate Degree Programs

Statistics (STAT)

Program Home Page

DAVID HUNTER, Head of the Department
326 Thomas Building
814-865-1348

 

Degrees Conferred:

 

The Graduate Faculty

 

 

The Program

Graduate instruction and research opportunities are available in most areas of statistics and probability, including linear models, nonparametric statistics, robustness, statistical computing, analysis of count data, multivariate analysis, experimental design, reliability, stochastic processes and probability (applied and theoretical), distribution theory, statistical ecology, and biometrics.

Graduate students can gain practical experience in the application of statistical methodology through participation in the department's statistical consulting center and collaborative research activities. In addition, collaborative projects with other departments provide longer term experience and support for selected students. Most students gain valuable teaching experience by assisting in the teaching and grading of courses. In addition, Ph.D. students with proper qualifications can receive support for teaching undergraduate courses.

The Master of Applied Statistics (M.A.S.) program is a professional degree designed to provide training in statistics focused on developing data analysis skills, and exploration of all core areas of applied statistics, without going deeply into the mathematical statistics foundations. It aims to provide its graduates with broad knowledge in a wide range of statistical application areas.

The Doctor of Philosophy (Ph.D.) and Master of Science (M.S.) degrees in Statistics are designed for advanced studies in applied and theoretical statistics. Special emphases include biostatistics, statistical ecology, environmental statistics, genometrics, biometrics and statistical computation. The M.S. degree is appropriate preparation for the department's Ph.D. degree.

Admission Requirements

Admission requirements listed here are in addition to requirements stated in the GENERAL INFORMATION section of the Graduate Bulletin.

Scores from the Graduate Record Examinations (GRE), or from a comparable substitute examination accepted by the Statistics graduate program, are required for admission.

While applications from all students (including those who already have done graduate work) are reviewed, completion of a standard calculus sequence is regarded as a prerequisite. Students with a 3.00 or better junior/senior average (on a 4.00 scale) and with appropriate course backgrounds will be considered for admission. The best-qualified applicants will be accepted up to the number of spaces that are available for new students. Exceptions to the minimum 3.00 grade-point average may be made for students with special backgrounds, abilities, and interests. Students hoping to earn a Ph.D. in statistics may apply directly to the Ph.D. program without need for a master's degree.

Degree Requirements

Requirements listed here are in addition to requirements stated in the DEGREE REQUIREMENTS section of the Graduate Bulletin.

Professional Master of Applied Statistics Requirements

For the M.A.S. degree, a minimum of 30 credits and a minimum grade-point average of 3.0 are required for graduation. Of the 30 credits, 24 must be courses from the Statistics department and 21 must be at the 500 level. The student must complete 6 credits in applied statistics (STAT 501, STAT 502), 6 credits in mathematical statistics (STAT 414, STAT 415) and 3 credits in statistical consulting (STAT 580 and 581). For all M.A.S. students, the STAT 581 course will have a comprehensive written project report required as part of the course, which serves as the culminating experience. To complete the remaining credit requirements, a student can select 9-15 credits from the following applied statistics courses: STAT 464, STAT 480, STAT 500, STAT 503, STAT 504, STAT 505, STAT 506, STAT 507, STAT 509, and STAT 510. In addition, students with suitable backgrounds may choose up to 6 credits from a departmental list of additional courses with approval from their adviser.

Master of Science Degree Requirements

For the M.S. degrees, a student must complete at least 30 credits, including at least 27 at the 500 or 600 level; 21 of the 27 500-level credits must be formal course work from the department of Statistics. A student must complete 6 credits in applied statistics (STAT 511, STAT 512), 6 credits in mathematical statistics (STAT 513, STAT 514), 3 credits in stochastic processes (STAT 515) and 3 credits in statistical consulting (STAT 580 and 581). The student must also pass a written master's qualifying examination taken at the end of the first year. Finally, an M.S. student must register for at least 6 credits of thesis research (600 or 610) and submit a thesis. The thesis must be accepted by the advisers, a second reader, the head of the graduate program, and the Graduate School.

Doctoral Degree Requirements

The Department of Statistics requires a minimum total of 48 postbaccalaureate credits for the Ph.D. At least 42 credits, exclusive of the dissertation, must be in Statistics. Course work accepted for the M.S. in Statistics at Penn State will count toward the department’s 48-credit requirement. In the case of students who have earned credits in an advanced degree program at another university or in another department at Penn State, a maximum of 24 credits may count toward the 48-credit departmental requirement, subject to departmental approval.

For the Ph.D. degree, a student in Statistics must complete at least 48 credits, of which at least 42 must be STAT and at most three credits can be at the 400 level. In addition to the 18 credits of core course requirements from the first year (STAT 511, STAT 512, STAT 513, STAT 514, STAT515, STAT 553), a Ph.D. student in Statistics must complete an additional 12 credits in advanced probability (STAT 517, 3 credits), statistical inference (STAT 561, 3 credits), statistical consulting (STAT 580, 2 credits, and STAT 581, 1 credit), colloquium (STAT 590, 2 credits) and teaching statistics (STAT 592, 1 credit), as well as 18 credits of electives taken from STAT 518, STAT 544, STAT 552, STAT 562, STAT 565, or other courses approved by the Graduate Studies Committee. The student also must pass a written Ph.D. candidacy exam, typically at the end of the first year, and a comprehensive exam given at the end of the third year. There are two ways for students to complete their comprehensive examination. Typically, both written and oral components of the comprehensive involve the defense of a dissertation proposal evaluated by the doctoral committee. Alternatively, the student may have a written and oral comprehensive exam focusing on at least two key areas in Statistics. The examination focuses on the dissertation prospects and the student’s preparation to undertake dissertation research, and is evaluated by the doctoral committee. A written and oral defense of a dissertation proposal would then occur at a later stage as per committee’s recommendation.  Students must have their dissertation proposal approved as specified in the Department of Statistics Graduate Student Handbook. The candidate then must submit an acceptable Ph.D. dissertation and pass a final oral examination (the dissertation defense). The dissertation must be accepted by the doctoral committee, the head of the graduate program, and the Graduate School.

The Ph.D. in Statistics offers concentrations in Biometrics, Biostatistics, Environmental Statistics, and Genometrics. The course and the examination requirements remain the same under these concentrations, however, the student must take 15 credits of electives from a list of courses identified by the concentration.

Doctoral Minor in Statistics Requirements

The Department of Statistics has three possible paths for a Doctoral Minor in Statistics:

  • Path 1: STAT/MATH 414 and 415 and at least three 500-level courses from the department.
  • Path 2: Five or more courses totaling 15 credits at the 500-level from the department. Stat 464 may also count toward the 15 credits.
  • Path 3: Four 500-level courses totaling 12 credits from the department and one additional course of 3 credits approved by the department head or graduate studies chair.

Please note: STAT 500 will not be counted toward the Doctoral Minor in Statistics under any path.

For all paths, a 3.5 GPA is required in the courses to be counted toward the minor. Completion of one of the paths listed above, with the specified grade-point average, and the signature on the Graduate Minor Program form constitutes approval of the Minor in Statistics. Official requests to add a minor to a doctoral candidate’s academic record must be submitted to Graduate Enrollment Services prior to establishment of the doctoral committee and prior to scheduling the comprehensive examination. At least one graduate faculty member from the minor field must be on the candidate’s doctoral committee.

Dual-Title Ph.D. and M.S. in Statistics and Operational Research


The Operations Research dual-title degree program is administered by an Operations Research committee, which is responsible for management of the program. The program enables students from diverse graduate programs to attain and be identified with the tools, techniques, and methodology of operations research, while maintaining a close association with areas of application. Operations research is the analysis--usually involving mathematical treatment--of a process, problem, or operation to determine its purpose and effectiveness and to gain maximum efficiency. To pursue a dual-title degree under this program option the student must apply to the Graduate School and register through one of the approved graduate programs.

Admission Requirements

Requirements listed here are in addition to requirements stated in the GENERAL INFORMATION section of the Graduate Bulletin.
Students must apply and be admitted to the graduate program in Statistics and the Graduate School before they can apply for admission to the dual-title degree program. Students must apply for enrollment into the dual-title Ph.D. in Operations Research prior to taking their candidacy exam in Statistics. Students are encouraged to submit their application forms as early as possible, and not later than at least two semesters before their intended date of graduation. The “Request for Dual-Title Degree in Operations Research” form must be filled out in consultation with the Graduate Coordinator in the Statistics Department and submitted to the Chair of the Operations Research Program.
For the M.S. dual-title degree in Operations Research, in addition to those prescribed by the graduate major program, prerequisites for acceptance to the program without deficiency include the following or their equivalent: MATH 140, MATH 141, MATH 220; CMPSC 101; and 3 credits of probability and statistics. The “Request for Masters Dual-Title Degree in Operations Research” form must be filled out.
For the Ph.D. dual-title degree in Operations Research, in addition to those prescribed by the graduate major program, prerequisites for acceptance to the program without deficiency include the following or their equivalent: MATH 401, MATH 436; CMPSC 101; and 3 credits of probability and statistics. The “Request for PH.D. Dual-Title Degree in Operations Research” form must be filled out.

Degree Requirements

Requirements listed here are in addition to requirements stated in the DEGREE REQUIREMENTS section of the Graduate Bulletin.
To qualify for the dual-title degree, students must satisfy the requirements of the Ph.D. in Statistics. In addition, they must satisfy the requirements described below, as established by the Operations Research committee.
For the M.S. dual-title degree in Operations Research, the minimum requirements are: 6 credits in stochastic/statistical methods, including a minimum of 3 credits in each of the areas of statistical methods and stochastic processes; 6 credits in optimization, including a minimum of 3 credits in linear programming; 3 credits in computational methods; and 3 credits in applications/specialization. A minimum of 9 credits must be in the 500 series. Particular courses may satisfy both the graduate major program requirements and those in the Operations Research program. The supervisor of the master’s thesis must be a member of the graduate faculty recommended by the chair of the program granting the degree and approved by the Operations Research committee as qualified to supervise thesis work in operations research.
The minimum requirements for the Ph.D. dual-title degree in Operations Research are: 9 credits in stochastic/statistical methods, including a minimum of 3 credits in each of the areas of statistical methods and stochastic processes; 9 credits in optimization, including a minimum of 3 credits in linear programming; 6 credits in computational methods, including a minimum of 3 credits in simulation; and 12 credits in applications/specialization. A minimum of 18 credits must be in the 500 series, and particular courses may satisfy both the graduate major program requirements and those in the Operations Research program.
Candidacy Exam
The dual-title degree will be guided by the Candidacy Exam procedure of the Statistics graduate program. The candidacy exam for the dual-title degree may be given after at least 18 postbaccalaureate credits have been earned in graduate courses. Because students must first be admitted to a graduate major program of study before they may apply to and be considered for admission into a dual-title graduate degree program, dual-title graduate degree students may require an additional semester to fulfill requirements for both areas of study and, therefore, the candidacy examination may be delayed one semester beyond the normal period allowable. Operations Research must be integrated into the student’s candidacy examination, and it may require additional examination beyond the one required by Statistics in order to assess whether the student should be admitted into Ph.D. candidacy in both Statistics and Operations Research. In accordance with Graduate Council policy, the candidacy committee must include at least one member of the Operations Research graduate faculty. Faculty members who hold appointments in both programs’ graduate faculty may serve in a combined role.

Doctoral Committee Composition

The doctoral committee must conform to all requirements of the primary program and the Graduate Council. In accordance with Graduate Council policy, the doctoral committee of a Statistics and Operations Research dual-title doctoral degree student must include at least one member of the Operations Research graduate faculty. Faculty members who hold appointments in both programs’ graduate faculty may serve in a combined role.

If the chair of the committee representing Statistics is not also a member of the graduate faculty in Operations Research, the member of the committee representing Operations Research must be appointed as co-chair.

Comprehensive Exam

After completing all course work, doctoral candidates for the dual-title doctoral degree in Statistics and Operations Research must pass a comprehensive examination that includes written and oral components.
There are two ways for students to complete their comprehensive examination.
Typically, both written and oral components of the comprehensive examination involve the defense of a dissertation proposal, which must contain core Statistics content and substantial Operations Research content, and is evaluated by the doctoral committee. The Operations Research representative(s) on the student’s doctoral committee will participate in the evaluation of the comprehensive examination.
Alternatively, the student may have a written and oral comprehensive exam focusing on at least two key areas in Statistics with content from Operations Research (acting as a first minor field). The examination focuses on the dissertation prospects and the student’s preparation to undertake dissertation research, and is evaluated by the doctoral committee. The Operations Research representative(s) on the student’s doctoral committee will develop questions for and participate in the evaluation of the comprehensive examination. A written and oral defense of a dissertation proposal would then occur at a later stage as per committee’s recommendation.

Dissertation and Dissertation Defense

Upon completion of the doctoral dissertation, the candidate must pass a final oral examination (the dissertation defense) to earn the Ph.D. degree. Students enrolled in the dual-title program are required to write and orally defend a dissertation on a topic that reflects their original research and education in Statistics and Operations Research. The dissertation must be accepted by the doctoral committee, the head of the graduate program, and the Graduate School.

Dual-Title Doctoral Degree in Statistics and Social Data Analytics

Statistics doctoral students seeking to attain and be identified with an interdisciplinary array of tools, techniques, and methodologies for social data analytics, while maintaining a close association with statistics, may apply to pursue a dual-title Ph.D. in Statistics and Social Data Analytics.
Social data analytics is the integration of social scientific, computational, informational, statistical, and visual analytic approaches to the analysis of large or complex data that arise from human interaction. The dual-title Ph.D. aims to enable scientists who expand the capability of social data analytics, and use those capabilities creatively to answer important social scientific questions and to address grand social challenges, in both academic and nonacademic settings.

Admission Requirements

Requirements listed here are in addition to requirements stated in the GENERAL INFORMATION section of the Graduate Bulletin.
Students must apply and be admitted to the graduate program in Statistics and the Graduate School before they can apply for admission to the dual-title degree program. Applicants interested in the dual-title degree program may make their interest in the program known clearly on their applications to Statistics and include remarks in their statement of purpose that address the ways in which their research and professional goals in statistics reflect an expanded interest in Social Data Analytics-related research.
To apply to the dual-title doctoral Ph.D. in Statistics and Social Data Analytics, a student must submit a letter of application and transcript, which will be reviewed by the Social Data Analytics Program. An applicant must have a minimum grade-point average of 3.0 (on a 4.0 point scale) to be considered for enrollment in the dual-title degree program. Students must apply for enrollment into the dual-title Ph.D. in Social Data Analytics prior to obtaining candidacy in Statistics.

Degree Requirements

Requirements listed here are in addition to requirements stated in the DEGREE REQUIREMENTS section of the Graduate Bulletin.
To qualify for the dual-title degree, students must satisfy the requirements of the Ph.D. in Statistics. In addition, they must satisfy the requirements described below, as established by the Social Data Analytics Committee. Within this framework, final course selection is determined by the student in consultation with academic advisers from their home department and Social Data Analytics.

Course Work

The minimum course work requirements for the dual-title Ph.D. in Statistics and Social Data Analytics are as follows:

  • Course work and other requirements for the Ph.D. in Statistics.
  • SO DA 501 (3 credits)
  • SO DA 502 (3 credits)
  • 12 or more elective credits in Social Data Analytics from a list of courses maintained by the Social Data Analytics Committee. Collectively the elective credits must satisfy the following requirements:
    • (A) Core analytics distribution. 3 or more credits in courses focused on statistical learning, machine learning, data mining, or visual analytics. Courses approved as meeting this requirement are designated (A) on the list of approved electives.
    • (Q) Quantification distribution. 6 or more credits in courses focused on statistical inference or quantitative social science methodology. Courses approved as meeting this requirement are designated (Q) on the list of approved electives. (A Statistics Ph.D. student would typically satisfy this distribution requirement as a function of completing the requirements of the Statistics Ph.D.)
    • (C) Computational / informational distribution. 6 or more credits in courses focused on computation, collection, management, processing, or interaction with electronic data, especially at scale. Courses approved as meeting this requirement are designated (C) on the list of approved electives.
    • (S) Social distribution. 6 or more credits in courses with substantial content on the nature of human interaction and/or the analysis of data derived from human interaction and/or the social context or ethics or social consequences of social data analytics. Courses approved as meeting this requirement are designated (S) on the list of approved electives. (A Statistics Ph.D. student would typically satisfy this distribution requirement as a function of completing the requirements of the Statistics Ph.D.)
    • Cross-departmental distribution.
      • 3 or more credits in approved courses with the prefix STAT or that of a primarily social science department. (A Statistics Ph.D. student would typically satisfy this distribution requirement as a function of completing the requirements of the Statistics Ph.D.)
      • 3 or more credits in approved courses with the prefix IST, GEOG, or that of a primarily computer science or engineering department.
      • 6 or more credits in approved courses outside Statistics.
      • 3 or fewer credits in approved courses at the 400-level.

Students are encouraged to take interdisciplinary courses that carry multiple (A), (Q), (C), (S) designations, as well as to select SO DA electives that also meet STAT requirements. In particular, the 12 elective SO DA credits can be met with as few as 6 credits of appropriately chosen course work. Conversely, 6 credits of SO DA course work, including SO DA 501 and SO DA 502, can be used to meet the STAT elective requirement. Within this framework, final course selection is determined by the student in consultation with academic advisers from Statistics and Social Data Analytics. (There are no formal maxima for the number of double-counted credits. For those meeting the SO DA elective requirement with the minimum of 12 credits, the outside-program minimum effectively limits the number of primary degree STAT credits that count toward SO DA at 6. For those meeting STAT elective requirements with the minimum of 18 credits, the 12 credit STAT minimum effectively limits the number of SO DA credits that count toward STAT at 6.)
Candidacy Exam
The dual-title degree will be guided by the Candidacy Exam procedure of the Statistics graduate program. The candidacy exam for the dual-title degree may be given after at least 18 postbaccalaureate credits have been earned in graduate courses. Because students must first be admitted to a graduate major program of study before they may apply to and be considered for admission into a dual-title graduate degree program, dual-title graduate degree students may require an additional semester to fulfill requirements for both areas of study and, therefore, the candidacy examination may be delayed one semester beyond the normal period allowable. There will be a single candidacy examination to assess whether the student should be admitted into Ph.D. candidacy in both Statistics and Social Data Analytics. In accordance with Graduate Council policy, the candidacy committee must include at least one member of the Social Data Analytics graduate faculty. Faculty members who hold appointments in both programs’ graduate faculty may serve in a combined role.

The Social Data Analytics Program maintains a list of recommended background and skills that it recommends students have in place by the time they begin the interdisciplinary course work required to complete the Social Data Analytics degree. The candidacy exam is the appropriate setting for assessing the student’s preparation for the interdisciplinary work of the dual-title Ph.D. in Statistics and Social Data Analytics.

Doctoral Committee Composition

The doctoral committee must conform to all requirements of the primary program and the Graduate Council. In accordance with Graduate Council policy, the doctoral committee of a Statistics and Social Data Analytics dual-title doctoral degree student must include at least one member of the Social Data Analytics graduate faculty. Faculty members who hold appointments in both programs’ graduate faculty may serve in a combined role.

If the chair of the committee representing Statistics is not also a member of the graduate faculty in Social Data Analytics, the member of the committee representing Social Data Analytics must be appointed as co-chair.

Comprehensive Exam

After completing all course work, doctoral candidates for the dual-title doctoral degree in Statistics and Social Data Analytics must pass a comprehensive examination that includes written and oral components.
There are two ways for students to complete their comprehensive examination.
Typically, both written and oral components of the comprehensive examination involve the defense of a dissertation proposal, which must contain core Statistics content and substantial Social Data Analytics content, and is evaluated by the doctoral committee. The Social Data Analytics representative(s) on the student’s doctoral committee will participate in the evaluation of the comprehensive examination.
Alternatively, the student may have a written and oral comprehensive exam focusing on at least two key areas in Statistics with content from Social Data Analytics (acting as a first minor field). The examination focuses on the dissertation prospects and the student’s preparation to undertake dissertation research, and is evaluated by the doctoral committee. The Social Data Analytics representative(s) on the student’s doctoral committee will develop questions for and participate in the evaluation of the comprehensive examination. A written and oral defense of a dissertation proposal would then occur at a later stage as per committee’s recommendation.

Dissertation and Dissertation Defense

Upon completion of the doctoral dissertation, the candidate must pass a final oral examination (the dissertation defense) to earn the Ph.D. degree. Students enrolled in the dual-title program are required to write and orally defend a dissertation on a topic that reflects their original research and education in Statistics and Social Data Analytics. The dissertation must be accepted by the doctoral committee, the head of the graduate program, and the Graduate School.

 

Integrated B.S. in Statistics and Master of Applied Statistics (M.A.S.)

The Integrated Undergraduate-Graduate (IUG) degree with B.S. in Statistics and Master of Applied Statistics (M.A.S.) is designed to be completed in five years. This integrated degree will enable a select number of highly qualified and career-oriented students to obtain training in statistics focused on developing data analysis skills and exploration of core areas of applied statistics at the undergraduate and graduate levels. The M.A.S. degree is a professional master's degree that emphasizes applications and does not provide as much training in the mathematical and statistical theory. The degree prepares students with interests in mathematics, computation, and the quantitative aspects of science for careers in industry and government as statistical analysts. Research divisions in the pharmaceutical industry, quality control and quality engineering divisions in manufacturing companies, clinical research units, corporate planning and research units, and other data-intensive positions require persons with training in mathematics, computation, database management, and statistical analysis, which this program will provide.

Application Process

The number of openings in the integrated B.S./M.A.S. program is limited. Students must apply to and meet the admission requirements of the Graduate School, as well as the graduate program in which they intend to receive their master’s degree. Admission will be based on specific criteria and the recommendation of faculty. Students shall be admitted to an IUG program no earlier than the beginning of the third semester of undergraduate study at Penn State (regardless of transfer or AP credits accumulated prior to enrollment) and no later than the end of the second week of the semester preceding the semester of expected conferral of the undergraduate degree, as specified in the proposed IUG plan of study. Applicants to the integrated program:

  • Must be enrolled in the Statistics B.S. program.
  • Must have completed at least 60 credits of the undergraduate degree program, including the two courses: STAT 414 and STAT 415.
  • Must submit a transcript and a statement of purpose.
  • Must present a departmental approved plan of study in the application process in consultation with the M.A.S. program director. The plan should cover the entire time period of the integrated program, and it should be reviewed periodically with an adviser as the student advances through the program.
  • Must be recommended by the chair of the department's undergraduate program committee.
  • Must be accepted into the M.A.S. program in Statistics.

Degree Requirements

Students in the IUG program must satisfy the requirements for both the B.S. and M.A.S. degrees; 120 credits are required for the B.S. and 30 credits for the M.A.S. The following twelve credits (number of credits in parentheses) can apply to both B.S. and M.A.S. degrees; six of these are at the 500 level:

STATISTICS (STAT)
414. Introduction to Probability Theory (3)
415. Introduction to Mathematical Statistics (3)
501. Regression Methods (3)
502. Analysis of Variance and Design of Experiments (3)


If students accepted into the IUG program are unable to complete the M.A.S. degree, they are still eligible to receive their undergraduate degree if all the undergraduate degree requirements have been satisfied.

 

Integrated B.A./B.S. in Mathematics and Master of Applied Statistics (M.A.S.)

The Integrated Undergraduate-Graduate (IUG) degree with B.A./B.S. in Mathematics and Master of Applied Statistics (M.A.S.) is designed to be completed in five years. This integrated degree will enable a select number of highly qualified and career-oriented students to obtain training in statistics focused on developing data analysis skills, and exploration of core areas of applied statistics at the graduate levels in addition to an undergraduate degree in Mathematics. The M.A.S. degree is a professional master's degree that emphasizes applications. The degree prepares students with interests in mathematics, computation, and the quantitative aspects of science for careers in industry and government as statistical analysts. Research divisions in the pharmaceutical industry, quality control, and quality engineering divisions in manufacturing companies, clinical research units, corporate planning and research units, and other data intensive positions require persons with training in mathematics, computation, database management, and statistical analysis, which this program will provide.

Application Process

The number of openings in the integrated B.A./B.S. and M.A.S. program is limited. Students must apply to and meet the admission requirements of the Graduate School, as well as the graduate program in which they intend to receive their master’s degree. Admission will be based on specific criteria and the recommendation of faculty. Students shall be admitted to an IUG program no earlier than the beginning of the third semester of undergraduate study at Penn State (regardless of transfer or AP credits accumulated prior to enrollment) and no later than the end of the second week of the semester preceding the semester of expected conferral of the undergraduate degree, as specified in the proposed IUG plan of study. Applicants to the integrated program:

  • Must be enrolled in the Mathematics B.A./B.S. program.
  • Must have completed at least 60 credits of the undergraduate degree program including the two courses: STAT 414 and STAT 415.
  • Must submit a transcript and a statement of purpose.
  • Must present a departmental approved plan of study in the application process in consultation with the M.A.S. program director. The plan should cover the entire time period of the integrated program, and it should be reviewed periodically with an adviser as the student advances through the program.
  • Must be recommended by the chair of Mathematics Department's undergraduate program committee. Two additional recommendation letters must be sent to the M.A.S. admissions committee.
  • Must be accepted to the M.A.S. program in Statistics.

 

Degree Requirements

Students in the IUG program must satisfy the requirements for both the B.A./B.S. and M.A.S. degrees; 120 credits are required for the B.A./B.S. and 30 credits for the M.A.S. The following twelve credits (number of credits in parentheses) can apply to both B.A./B.S. and M.A.S. degrees, six of these are at the 500 level:

STATISTICS (STAT)
414. Introduction to Probability Theory (3)
415. Introduction to Mathematical Statistics (3)
501. Regression Methods (3)
502. Analysis of Variance and Design of Experiments (3)

If students accepted into the IUG program are unable to complete the M.A.S. degree, they are still eligible to receive their undergraduate degree if all the undergraduate degree requirements have been satisfied.

Student Aid

Graduate assistantships available to students in this program and other forms of student aid are described in the STUDENT AID section of the Graduate Bulletin. GRE scores are required for consideration for assistantships. Students on graduate assistantships must adhere to the course load limits set forth in the Graduate Bulletin.

Courses

Graduate courses carry numbers from 500 to 599 and 800 to 899. Advanced undergraduate courses numbered between 400 and 499 may be used to meet some graduate degree requirements when taken by graduate students. Courses below the 400 level may not. A graduate student may register for or audit these courses in order to make up deficiencies or to fill in gaps in previous education but not to meet requirements for an advanced degree.

STATISTICS (STAT) course list

 

 

Last Revised by the Department: Summer 2016

Blue Sheet Item #: 44-07-000

Review Date: 6/28/2016

IUG PROGRAM - B.S. in Statistics and Master of Applied Statistics
Last Revised by the Department: Summer Session 2003
Blue Sheet Item #: 31-05-138

IUG PROGRAM - B.A./B.S. in Mathematics and Master of Applied Statistics
Last Revised by the Department: Fall Semester 2006
Blue Sheet Item #: 34-06-361 and 34-06-361A
Review Date: 4/11/06

REVISED BY SENATE: 1/5/06 [course number update]

Facuty linked: 6/27/14

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