Data Analysis + Applied Statistics: Blacksburg Campus

The Master of Arts in Data Analysis and Applied Statistics degree comprises 30 credits, distributed among applied statistics and analytical courses from a variety of departments. A basic set of courses is required as part of the core program. The core program will consist of courses comprising 18 credit hours in applied statistics, regression methods, design of experiments, basic theoretical statistics, professional development in communication and collaboration, and a final project and examination required of all students. The remaining 12 credit hours are from electives from the Department of Statistics and/or other departments.

Core Curriculum

(18 credits; required of all students)

STAT 5204G: Experimental Design: Concepts and Applications (3 cr)
STAT 5214G: Advanced Methods of Regression Analysis (3 cr)
STAT 5615/5616: Statistics in Research I and II (6 cr)
STAT 5024: Communication in Statistical Collaborations (3 cr)
STAT 5904: Project and Report (3 cr)

Restricted Electives

(12 credits; required of all students)

Statistics

STAT 5054: Introduction to Statistical Computing (3 cr)
STAT 5106G: Theoretical Statistics II (3 cr)
STAT 5154: Statistical Computing for Data Analytics (3 cr)
STAT 5234: Experimental Design for Data Science (3 cr)
STAT 5504G: Advanced Applied Multivariate Methods (3 cr)
STAT 5514G: Advanced Contingency Tables (3 cr)
STAT 5524G: Sample Survey Methods (3 cr)
STAT 5525 (CS 5525): Data Analytics (3 cr)
STAT 5526 (CS 5526): Data Analytics (3 cr)
STAT 5474: Statistical Theory of Quality Control (3 cr)
STAT 5664: Applied Statistical Time Series Analysis for Research Scientists (3 cr)

Agricultural and Applied Economics/Economics

AAEC/ECON 5125: Empirical Research Methods in Economics I (3 cr)
AAEC/ECON 5126: Empirical Research Methods in Economics II (3 cr)
AAEC/ECON 5946: Econometric Theory and Practice (3 cr)
AAEC/ECON 6554: Panel Data Econometrics (3 cr)

Educational Research and Evaluation

EDRE 5404: Foundations of Educational Research and Evaluation (3 cr)
EDRE 5644: Questionnaire Design and Survey Research in Education (3 cr)
EDRE 6634: Advanced Statistics for Education (3 cr)
EDRE 6654: Multivariate Statistics for Applications to Educational Problems (3 cr)
EDRE 6664: Application of Structural Equations in Education (3 cr)
EDRE 6794: Advanced Topics in Educational Research (3 cr)
EDRE 6605: Quantitative Research Methods in Education (3 cr)
EDRE 6606: Quantitative Research Methods in Education (3 cr)
EDRE 6694: Hierarchical Linear Modeling (3 cr)

Human Development

HD 5514: Research Methods (3 cr)
HD 6514: Advanced Research Methods (3 cr)
HD 6524: Current Topics in Advance Research Methods (3 cr; co-enroll with HD 6514)

Public Administration and Public Affairs

PAPA 5214: Research methods (3 cr)
PAPA 6524: Advanced Research Methods (3 cr)

Psychology

PSYC 5134: Advanced Psychometric Theory (3 cr)
PSYC 5315: Research Methods (3 cr)
PSYC 5316: Research Methods (3 cr)
PSYC 6014: Quantitative Topics in Industrial and Organizational Psychology (3 cr)

Political Science

PSCI: 5115: Research Methods (3 cr)

Geography

GEOG 5034: Analysis of Spatial Data (3 cr)
GEOG 5314: Advanced Spatial Analysis in Geographic Information Systems (3 cr)

Fisheries and Wildlife Sciences

FIW 5514: Fish Population Dynamics and Modeling (3 cr)
FIW 5214: Vertebrate Population and Habitat Analysis (3 cr)
FIW 6514: Risk Assessment and Decision Analysis for Fisheries & Conservation Biology (3 cr)
FIW 6114: Applied Conservation Genetics (3 cr)

Forest Resources and Environmental Conservation

FOR 5494: Natural Resource Research Procedures (3 cr)
FOR 5224: Forest Biometry (3 cr)

Sociology

SOC 5204: Data Analysis (3 cr)
SOC 5214: Research Methods (3 cr)
SOC 6204: Survey Research Methods (3 cr)

Committee and Exam

Each student in the program will have a three-person DAAS committee, consisting of at least one faculty member from the Department of Statistics and two other members (from any participating department on campus), all selected by the student. The chair of this committee must be a faculty member in the Department of Statistics, but faculty from other degree programs are certainly able to co-chair student committees. It is the responsibility of this committee to develop, along with the student’s input, a proper plan of study for the student that incorporates a breath of topics, while also meeting the academic and professional goals of the student.

To complete the requirements for the M.A. degree in DAAS, the student must pass a final examination (STAT 5904: Project and Report). The final examination would consist of a project that will evaluate the student on a M.A.-level command of statistical techniques. The topic for the project would be determined by the student's DAAS Committee and evaluated by this committee on a pass/fail basis. The student will present the completed project to the committee in both written and oral format. The project should be presented and evaluated in the semester in which the student plans on receiving the M.A. degree in DAAS. A majority vote by the committee members determines the result. Should the student not pass the exam, they will be required to take the exam a second time although not in the same semester. The student may only take the exam twice. Failing the exam a second time results in dismissal from the program.

The Project and Report examination must be scheduled through the Virginia Tech Graduate School at least 2 weeks in advance in accordance with their exam scheduling policies. The exam scheduling policy can be found at https://secure.graduateschool.vt.edu/graduate_catalog/policies.htm?policy=002d14432c654287012c6542e3630013.

Sample Plan of Study

Below is a sample plan of study for a student entering the program with a B.S. degree.

First Year

Fall Semester

STAT 5615 (3)
Restrictive Elective (3)
Total credits: 6

Spring Semester

STAT 5616 (3)
STAT 5024 (3)
Restricted Elective (3)
Restricted Elective (3)
Total credits: 12

Second Year