Dr. Matthew Dull

Office: 703-706-8117
Cell: 202-821-3807

Email: mdull@vt.edu

Description
This intermediate quantitative and qualitative empirical methods workshop focuses on the design and execution of an original research project. Over the course of the semester participants will develop an empirical paper or research design on a topic in public policy or public administration. Coursework consists of the following elements:

1) A 1-page draft research proposal circulated to course participants via Blackboard on or before Monday 1/28 and a revised research proposal posted on or before Monday 2/11;
2) Facilitation of one class session around a specific research method or model, selecting the topic and readings in consultation with the course instructor;
3) A short annotated bibliography reviewing examples of research applying the method or model the participant has selected, distributed via Blackboard on the Monday prior to the class the participant facilitates;
4) Draft research designs due Monday 3/17 and Monday 4/14;
5) Final empirical paper or research design posted to Blackboard on or before Sunday 5/4;
6) Finally, course participants are expected to play an active role in the course, offering feedback and helping to shape one another’s projects.

In general, readings will be made available in electronic format on Blackboard. However, below are a handful of books we will be reading more or less in full. I recommend you obtain hard copies:

• Martha S. Feldman, 1989. Order without design: information production and policy making. Stanford, Calif., Stanford University Press.
• Martha S. Feldman, 1995. Strategies for Interpreting Qualitative Data. Sage.
• Laura Jensen, 2003. Patriots, Settlers, and the Origins of American Social Policy. Cambridge.
• Jane E. Miller, 2005. The Chicago guide to writing about multivariate analysis. Chicago, University of Chicago Press. ISBN: 0226527832. (Paperback)
• Edward R. Tufte, 2001. The Visual Display of Quantitative Information. Graphics Press.

Prerequisites for the course are PAPA 6514 or equivalent and familiarity with concepts covered in a standard introductory statistics course. Students are encouraged to contact with the instructor with any questions regarding prerequisites or the appropriateness of the course for their needs. If you have not recently taken a statistics course, it is strongly recommended that you review a basic statistics text. One text that is clear and available used online is: Robert M. Kaplan, 1986. Basic Statistics for the Behavioral Sciences. Allyn and Bacon, Inc.

Course Schedule – Getting Started
1. Course Introduction (1/17)
Please read the following two articles prior to our first meeting:

• Joe Soss. 1999. “Lessons of Welfare: Policy Design, Political Learning, and Political Action.” American Political Science Review. 93(2): 363-80.
• R. K. Rethemeyer. 2007. “Policymaking in the Age of Internet: Is the Internet Tending to Make Policy Networks More or Less Inclusive?” Journal of Public Administration Research and Theory. 17: 259-284.

Recommended

• Herbert M. Kritzer, 1996. "The Data Puzzle: The Nature of Interpretation in Quantitative Research." American Journal of Political Science 40(1): 1-32.
• Joe Soss and Sanford F. Schram. 2007. “A Public Transformed? Policy Reform as Policy Feedback. “ American Political Science Review.
• Suzanne Mettler, 2002. “Bringing the State Back in to Civic Engagement: Policy Feedback Effects of the G.I. Bill for World War II Veterans.” The American Political Science Review 96(2): 351-365.
• Mark Granovetter. 2005.” The Impact of Social Structure on Economic Outcomes.” The Journal of Economic Perspectives, Vol. 19, No. 1.Winter, pp. 33-50.

2. Representing Data (1/24)

• Miller, 1-4. Chava Frankfort-Nachmias and David Nachmias, 2000. “Measurement,” (Ch. 7) Research Methods in the Social Sciences.
• Edward Tufte, 2001. The Visual Display of Quantitative Information. Ch. 1, 4-6, 8-9
• Jonathan P. Kastellec and Eduardo L. Leoni. 2007. “Using Graphs Instead of Tables in Political Science.” Perspectives on Politics.

Recommended

• Theodore M. Porter, 1995. Trust in numbers: the pursuit of objectivity in science and public life. Princeton, N.J.: Princeton University Press.
• Robert Adcock and David Collier. 2001. “Measurement Validity: A Shared Standard for Qualitative and Quantitative Research.” American Political Science Review. 95: 529-46.
• Gelman, Pasarica, Dodhia. 2002. “Let’s Practice What We Preach: Turning Tables Into Graphics,” The American Statistician.

3. Modeling Missing Data (1/31)

• P. D. Allison. 2001. Missing data. Thousand Oaks, Calif., Sage Publications. Ch. 1-4.
• M. Dull. Results-Model Reform Leadership: Questions of Credibility and Commitment. Journal of Public Administration Research and Theory. Forthcoming.

4. Choice-based Models

• Kris Wernstedt, Peter B. Meyer, Anna Alberini. Attracting private investment to contaminated properties: The value of public interventions. Journal of Policy Analysis and Management. Volume 25, Issue 2, Date: Spring 2006, Pages: 247-369.
• Bryan Jones and Frank Baumgartner, 2005. “A Model of Choice in Public Policy.” Journal of Public Administration Research and Theory
• Gerd Gigerenzer, 1991. "From Tools to Theories: A Heuristic of Discovery in Cognitive Psychology." Psychological Review 98: 254-267.

Recommended

• Paul R. Portney, 1994. “The Contingent Valuation Debate: Why Economists Should Care,” Journal of Economic Perspectives, 8:4.
• T.H. Stevens, R. Belkner, D. Dennis, D. Kittredge, C. Willis. 2007. “Comparison of contingent valuation and conjoint analysis in ecosystem management.”
• Felix Schläpfer. 2007. “Contingent Valuation: A New Perspective,” Ecological Economics.
• Gerald F. Smith, 1995. “Classifying Managerial Problems: An Empirical Study of Definitional Content,” Journal of Management Studies, 32:5. September.
• John Conlisk, 2005. “Why Bounded Rationality,” Journal of Economic Literature.
• Joel M. Podolny. 199). "A Status-Based Model of Market Competition." The American Journal of Sociology 98(4): 829-872.

5. Strategies for Interpreting Qualitative Data:

• Martha Feldman Martha S. Feldman, 1995. Strategies for Interpreting Qualitative Data. Sage.
• Martha S. Feldman, 1989. Order without design: information production and policy making. Stanford, Calif., Stanford University Press.
• Martha S. Feldman, 2000. “Organizational Routines as a Source of Continuous Change,” Organization Science 11(6): 611-629.

Recommended

• Kaufman, H. (1960). The forest ranger, a study in administrative behavior. Baltimore,, Published for Resources for the Future by Johns Hopkins Press.
• Derthick, M. (1990). Agency under stress : the Social Security Administration in American government. Washington, D.C., Brookings Institution.

6. Narratives

• Kathe Callahan, Melvin J . Dubnick, and Dorothy Olshfski. 2006. “War Narratives: Framing Our Understanding of the War on Terror,” Public Administration Review. July/August.
• Malcolm Gladwell, 2007. “Dangerous Minds,” The New Yorker. Ospina, S. M. and J. Dodge (2005). It’s About Time: Catching Method Up to Meaning; The Usefulness of Narrative Inquiry in Public Administration Research. 65: 143-157.
• Dodge, J., S. M. Ospina, et al. (2005). Integrating Rigor and Relevance in Public Administration Scholarship: The Contribution of Narrative Inquiry. 65: 286-300.
• Ospina, S. M. and J. Dodge (2005). Narrative Inquiry and the Search for Connectedness: Practitioners and Academics Developing Public Administration Scholarship. 65: 409-423.

7. Interpreting History: Archival Data

• Laura Jensen, 2003. Patriots, Settlers, and the Origins of American Social Policy. Cambridge.

Recommended

• Fred I. Greenstein, The Hidden Hand Presidency. Johns Hopkins.
• D. Carpenter, 2001. The Forging of Bureaucratic Autonomy. Princeton.
• Paul Pierson, 1994. Dismantling the Welfare State? Reagan, Thatcher and the Politics of Retrenchment. Cambridge: Cambridge University Press.

office: 703.538.8477
home: 301.951.5291
e-mail: gbelli@vt.edu

Office: Room#438

CATALOGUE DESCRIPTION

 Multivariate statistical procedures presented in an applied research setting. Oriented toward the logical extension of univariate tests of significance and estimation procedures to multivariate problems. Emphasis is on understanding the techniques and their use via discussions of empirical research articles, plus consideration of outputs using existing computer software packages.

 Prerequisite: STAT/EDRE 6634 and STAT/EDRE 6644 (or equivalent regression & design courses).

 TEXTS
Required

Grimm, L.G. and Yarnold, P.R. (eds.) (1995) Reading and Understanding Multivariate Statistics. Washington, D.C.: The American Psychological Association.

Recommended, but not required

Grimm, L.G. and Yarnold, P.R. (eds.) (2000) Reading and Understanding MORE Multivariate Statistics. Washington, D.C.: The American Psychological Association.

(May be ordered from APA, 1-800-374-2721 or 202-336-5510)

 COMPUTER PROGRAMS and DATA
 

Students may choose any statistical software package, but most class examples will be demonstrated using SPSS or JMP. Both SPSS and LISREL outputs are provided in the textbook.

JMP is free for students.  Go to http://rmc.ncr.vt.edu, click on “tools” and find reference to JMP.

Course documents will be available for printing from Blackboard (log onto www.learn.vt.edu using your VT PID). If you do not use your VT email, PLEASE MODIFY IT SO THAT ANY MESSAGES WILL REDIRECT TO YOUR PERSONAL EMAIL.

ORGANIZATION OF COURSE

 Coverage of most techniques will be roughly as follows:

1)     Brief introduction to the analysis and its use via applications (through both text examples and articles). This will depend heavily on class discussions.

2)     Further explanation of theory and logic of the analysis via lecture and a review of outputs.

We will also review some fundamentals of univariate statistics (as needed), review data screening procedures, and end with an overview of some additional multivariate procedures. Nothing more than a background in basic algebra will be expected. In keeping with the notion of continuous quality improvement, modifications may be made depending on student input.

ASSIGNMENTS

MULTIVARIATE STATISTICS - Tentative Schedule

office: 703.538.8477
home: 301.951.5291
e-mail: gbelli@vt.edu

Office: Room#438

Catalogue description: This two-course sequence [EDRE 6606-6606] is designed to provide an overview of basic research design, measurement and statistical concepts in social and behavioral research. Emphasis will be placed on understanding the process of social and educational research in field settings, hands on experience of designing and conducting research and analysis of data.

EDRE 6606 (fall semester) – Intro to research methods and to descriptive and inferential statistics. The focus will be on experimental and quasi-experimental research designs and analyses used to compare group differences: t-tests, ANOVA, and ANCOVA.

EDRE 6606 (spring semester) – The research methods focus will be on non-experimental quantitative designs, survey research, and qualitative designs. The quantitative part of the course will deal with measurement issues and the statistical analyses often used with survey data and to explore relationships
between variables: correlation, regression, and chi-square analyses.

TEXT AND RESOURCES
1) Blackboard is used for course materials, announcements, email, etc.:
    a) From a web browser (Explorer, Netscape, Mozilla), go to the Blackboard site - http://learn.vt.edu
    b) logon using your VT PID and password
    c) click on EDRE 6606, which should be shown in your “List of Courses”
2) Text and Electronic Resources:
    Slavin, R.E. (2007). Educational Research in an Age of Accountability. Pearson Education Inc.
    Lowry, R. (1999-2008). Concepts and applications of inferential statistics. Retrieved October 10, 2007 from http://faculty.vassar.edu/lowry/webtext.html
    StatSoft Electronic Textbook (1984-2007). http://www.statsoft.com/textbook/stathome.html
    Stockburger, D. W. (1996-1998). Introductory statistics: Concepts, models, and applications. WWW Version 1.0
    Trochim, W. M. The Research Methods Knowledge Base, 2nd Edition. Internet WWW page, at URL: <http://www.socialresearchmethods.net/kb/). (version current as of August 16, 2004) A web resource for statistical and research information.
    Finding Published Instruments (http://www.apa.org/science/faq-findtests.html) A web guide for locating and using published and unpublished instruments:
American Psychological Association, Science Directorate (2002), FAQ/Finding Information About Psychological Tests.

3) Readings (Available in Blackboard. Additional readings will be posted during the semester.)
    a) Hutchinson, S.R. (2004) Survey Research. In K. deMarrais and S. D. Lapan (eds.) Foundation for research: Methods of inquiry in education and the social sciences (pp. 283-301). Hillsdale, NJ: Lawrence Erlbaum Associates.
    b) Robinson, D. H., Levin, J. R., Thomas, G. D., Pituch, K. A., & Vaughn, S. (2007). The incidence of “causal” statements in teaching-and-learning research journals. American Educational Research Journal, 44(2), 400-413.
4) Software: JMP Statistical Software; free for students through the Software Network.
Log on at the following site using your VT PID and password:
https://www.ita.vt.edu/Apps/WebObjects/NetSoftware and scroll down to: SAS JMP.
Note about Text: Slavin (2007) concludes every chapter with the following:
    • Research Navigator (Key terms & Activities)
    • Exercises
    • Further reading
Review these sections and use www.researchnavigator.com in studying for each chapter.
Additionally, consider using Google Scholar (http://scholar.google.com/) for finding articles (or go to
www.google.com; click on “more” and select “scholar” from the list.

COMMUNICATION
Blackboard email lists contain VT PIDs. IF YOU DO NOT USE YOUR VT EMAIL, PLEASE MODIFY IT SO THAT ANY MESSAGES WILL REDIRECT TO YOUR OWN ACCOUNT.
    • SENDING EMAIL – Please put EDRE 6606 in subject line.
    • SENDING ATTACHMENTS – Send files using the following format for file names:
EDRE6606-your last name-descriptive name for file.doc

COURSE STRUCTURE/GRADES:
 • The tenets of the Virginia Tech Graduate Honor Code will be strictly enforced in this course, and all graded assignments shall be subject to the stipulations of the Graduate Honor Code. For more information on the Graduate Honor Code, please refer to the GHS Constitution, located online at
http://fbox.vt.edu/studentinfo/gradhonor/

• Please note that ungraded assignments may (and probably should) be done with classmates. There will be three graded exams, whose formats will vary and could include short essays or  article reviews. Additional assignments will be given using JMP, the web, or articles. If you miss a deadline, assignments need to be turned in before the next class meeting, when the graded papers are returned to class. Final grade will be assigned based on total percentage points,
generally in the following manner, after adjusting for class average, which is usually a B.
95-100% - A 85-89% - B+ 70-74% - C+ Below 60% - F
90-94% - A- 80-84% - B 65-69% - C
75-79% - B- 60-64% - C

Accomodations

If you need adaptations or accommodations because of a disability (learning disability, attention deficit
disorder, psychological, physical, etc.); if you have emergency medical information to share with me; or if
you need special arrangements, please make an appointment with me as soon as possible.

Additional References
Bogdan, R.C. and Biklen, S.K. (1998). Qualitative research for education: An introduction to theory and methods. Boston: Allyn and Bacon.
Elmore, P.B. and Woehlke, P.L. (1997) Basic Statistics. NY: Longman.

Howell, D.C. (2002). Statistical Methods for Psychology (5th ed.). Pacific Grove, CA: Wadsworth
Publishing.
Pedhazur, E.J. and Schmelkin, L.P. (1991) Measurement, Design, and Analysis: An Integrated Approach.
NJ: Lawrence Erlbaum Associates, Publishers. (a great reference book; lots of detail)

Course Schedule
The following pages provide a tentative course schedule, which we will follow as closely as possible.
Modifications may be made throughout the semester.

office: 703.538.8477
home: 301.951.5291
e-mail: gbelli@vt.edu

Office: Room#454

Catalogue Description: This two-course sequence [EDRE 6605-6606] is designed to provide an overview of basic research design, measurement and statistical concepts in social and behavioral research. Emphasis will be placed on understanding the process of social and educational research in
field settings, hands on experience of designing and conducting research and analysis of data.

EDRE 6605 (fall semester) – Intro to research methods and to descriptive and inferential statistics. The focus will be on experimental and quasi-experimental research designs and analyses used to compare
group differences: t-tests, ANOVA, and ANCOVA. In addition to text an online materials, published research articles will be read and critiqued.

EDRE 6606 (spring semester) – The focus on research methods will be on non-experimental quantitative
designs, survey research, and qualitative designs. The quantitative part of the course will deal with
measurement issues and the statistical analyses often used with survey data and to explore relationships
between variables: correlation, regression, and chi-square analyses.

TEXT AND TEACHING AIDS
1) Blackboard: Course materials, announcements, discussion groups, email, etc. will be available on the Web via a program called “Blackboard” that allows for a number of online interactions. Do the following to familiarize yourself with what is available with it:
   a) open your web browser (Explorer, Netscape, etc.)
   b) go to the Blackboard site - http://learn.vt.edu
   c) logon using your VT PID and password
   d) click on EDRE 6605, which should be shown in your “List of Courses”
   e) familiarize yourself with the component parts – Review additional links under WEBSITE button.
2) Texts and Electronic Resources:
   a) Methods text: Slavin, R.E. (2007). Educational Research in an Age of Accountability. Pearson Education Inc.
   b) Statistics text: several online texts and resources will be used. URLs will be provided in class and via Blackboard.
3) Readings (Available in Blackboard. Additional readings will be posted during the semester.)
   a) Cross, L. H. & Belli, G. M, (2004) Experimental research to inform educational policy. In K. deMarrais and S. D. Lapan (eds.) Foundation for research: Methods of inquiry in education and the social sciences (pp. 329-351). Hillsdale, NJ: Lawrence Erlbaum Associates.
   b) Newman, M. & Edbourne, D. (2004). Improving the usability of educational research: Guidelines for the REPOrting of primary empirical research Studies in Education (The REPOSE Guidelines). Evaluation and Research in Education, 18(4), 201-212.
4) Software: JMP Statistical Software. We will have in-class demonstrations and hands on practice in the Computer Lab (room 102). JMP is a software environment for statistical computing and graphics, brought by the SAS Institute Inc. The University has currently an agreement with SAS, so that JMP
can be used for free by all faculty and graduate students through the Software Network. Log on at the following site using your VT PID and password:
https://www.ita.vt.edu/Apps/WebObjects/NetSoftware and scroll down to: SAS JMP 6.0.2
5) Important Note about Text: Slavin (2007) concludes every chapter with the following:
   • Research Navigator
       o Key terms
       o Activity
   • Exercises
   • Further reading
Please review these sections and use www.researchnavigator.com in studying for each chapter.
Additionally, consider using Google Scholar (http://scholar.google.com/) for finding articles (or go to
www.google.com; click on “more” and select “scholar” from the list.
6) Communication: Blackboard email lists contain VT PIDs. IF YOU DO NOT USE YOUR VT EMAIL, PLEASE MODIFY IT SO THAT ANY MESSAGES WILL REDIRECT TO YOUR OWN ACCOUNT.
   • SENDING EMAIL – Please put EDRE 6605 in subject line.
   • SENDING ATTACHMENTS – Send files using the following format for file names:
       EDRE6605-your last name-descriptive name for file.doc

COURSE STRUCTURE/GRADES:
The tenets of the Virginia Tech Graduate Honor Code will be strictly enforced in this course, and all graded assignments shall be subject to the stipulations of the Graduate Honor Code. For more information on the Graduate Honor Code, please refer to the GHS Constitution, located online at http://fbox.vt.edu/studentinfo/gradhonor/. Please note that ungraded assignments may (and probably should) be done with classmates. There will
be three graded exams, whose formats will vary and could include short essays or article reviews. Additional assignments will be given using JMP, the web, or articles. If you miss a deadline, assignments need to be turned in before the next class meeting, when the graded papers are returned to class. Final
grade will be assigned based on total percentage points, generally in the following manner, after adjusting for class average, which is usually a B.
95-100% - A 85-89% - B+ 70-74% - C+ Below 60% - F
90-94% - A- 80-84% - B 65-69% - C
75-79% - B- 60-64% - CAdditional

References – some textbooks used in the past
Elmore, P.B. and Woehlke, P.L. (1997) Basic Statistics. NY: Longman.
Howell, D.C. (2002). Statistical Methods for Psychology (5th ed.). Pacific Grove, CA: Wadsworth
Publishing.
Pedhazur, E.J. and Schmelkin, L.P. (1991) Measurement, Design, and Analysis: An Integrated Approach.
NJ: Lawrence Erlbaum Associates, Publishers. (a great reference book; lots of detail)

Additional References – supplemental and fun stuff found by previous students
Carr, J.J. (1994) A Crash Course in Statistics: An Innovative Book/Multimedia Approach to Collecting, Organizing, and Analyzing Data. Salana Beach, CA: High Text Publications Inc. (ncludes CD).
Gonick, L. & Smith, W. (1993) The Cartoon Guide to Statistics. NY: Harper Perennial.
Graham, A. (1994) Teach Yourself Statistics. Chicago, IL: NTC Publishing Group.
Hinton, P.R. (1995) Statistics Explained: A Guide for Social Science Students. NY: Routledge.
Langley, R. (1970) Practical Statistics Simply Explained. NY: Dover Publications, Inc.
Phillips, J.L. (1982) Statistical Thinking (2nd ed). NY: W.H. Freeman and Company.
Rowntree, D. (1981) Statistics Without Tears: A Primer for Non-Mathematicians. NY: Charles Scribner’s Sons.

Course Schedule
The following pages provide a tentative course schedule, which we will follow as closely as possible. Modifications may be made throughout the semester.

NVC 438

Tel: (703) 538 3767

lmili@vt.edu

PREREQUISITES: This course requires a basic knowledge in probability and statistics as covered in STAT 4714.

TEXTBOOKS: Alberto Leon-Garcia. Probability & Random Processes for Electrical Engineering. 3rd Edition, 2008, Prentice Hall. ISBN 0131471228.

OBJECTIVE: An introduction to probability theory, random variables, and stochastic processes with applications to the analysis of linear system response to random inputs. Emphasis will be placed on applications in communications, computer and radar systems.

OFFICE HOURS: Mondays: 7:00 - 8:00 PM, NVC 438 Thursdays: 2:00 – 4:00 PM, NVC 438

GRADING
Homework 30%
Midterm Test 35%
Final Exam 35%

HOMEWORK: Assigned homework will be collected in class on due time. Late homework will
be penalized.
MIDTERM TEST: The test will be in class, and open book/notes.
FINAL EXAM: The final exam will be of the take-home type.
BLACKBOARD: You are urged to consult regularly Blackboard to be informed about the latest announcements and to have access to posted course materials, assignments, and discussions.

HONOR SYSTEM: Honor system rules apply to all your work. It is your understanding that should be reflected in all work that you turn in. See http://ghs.grads.vt.edu/: “In working on projects and homework, discussion and cooperative learning on general topics is encouraged. Such discussion must be limited to general information such as lecture and text material. Using another student’s solution, design, implementation, or other specific results is strictly prohibited and is an honor code violation. Copying computer files or designs from any source is strictly prohibited and is an honor code violation. The midterm and final exams must be the work of the student. Consulting any other person except the instructor for this course about any aspect of an exam is strictly
prohibited and is an honor code violation. Ask the instructor if you ever have a question about what is acceptable or unacceptable sharing.”

DISABILITY ACCOMODATION: Reasonable accommodations are available for students who have documentation of a disability from a qualified professional. Students should contact the Services for Students with Disabilities (SSD). Any student with accommodations through the SSD Office should contact me during the first two weeks of the semester.

RELIGIOUS ACCOMODATION: If participation in some part of this class conflicts with your observation of specific religious holidays during the semester, please contact me during the first two weeks of class to make alternative arrangements.

ACCOMODATION FOR MEDICAL OR PERSONAL/FAMILY EMERGENCIES: If you miss class due to illness, especially in the case of an exam or some deadline, contact a professional in Schiffert Health Center. If deemed appropriate, documentation of your illness will be sent to the Dean’s Office for distribution to me. If you experience a personal or family emergency that necessitates missing class, contact the Dean of Students at (540) 231 3787.

NVC 438

Tel: (703) 538 3767

E-mail: lmili@vt.edu

PREREQUISITES: This course requires a basic knowledge in probability and statistics as covered in STAT 4714.

TEXTBOOKS: Class notes will be distributed throughout the semester.

REFERENCE BOOKS:

David C. Hoaglin, Frederick Mosteller, John W. Tukey. Understanding Robust and Exploratory Data Analysis. John Wiley, 1983. - F. R. Hampel et al.

Robust Statistics: The Approach Based on Influence Functions. John Wiley 1986. - R. G. Staudte and S. J. Sheather.

Robust Estimation and Testing. John Wiley 1990. - Peter J. Rousseeuw and Annick M. Leroy.

Robust Regression and Outlier Detection. John Wiley, 1987. - R. A. Maronna, R. D. Martin, and V. J. Yohai.

Robust Statistics-Theory and Methods. John Wiley, 2006. - A. Abur and A. G. Exposito.

Power System State Estimation-Theory and Implementation. Marcel Dekker, 2004. - J. Astola and P. Kuosmanen.

Fundamentals of Nonlinear Digital Filtering. CRC Press, 1997. - J. Baran. Statistics for Long-Memory Processes. Chapman & Hall, 1994. - K. Park and W. Willinger (Editors).

Self-Similar Network Traffic and Performance Evaluation. John Wiley, 2000.

OBJECTIVE: An introduction to optimal and robust estimation and filtering as applied to engineering problems such as speech processing, image processing, Internet data processing, detection in radar systems, system identification, measurement calibration, power system state estimation and load forecasting, and electric price forecasting.

OFFICE HOURS: Mondays: 7:00 – 8:00 PM, NVC 438 Wednesdays: 7:00 – 8:00 PM, NVC 438 Thursdays: 3:00 – 5:00 PM, NVC 438

GRADING: Homework 30% Midterm Test 35% Final Exam (Project) 35%

HOMEWORK: Assigned homework will be collected in class on due time. Late homework will be penalized.

MIDTERM TEST: The test will be in class, and open book/notes.

FINAL EXAM: The final exam will be of the take-home type. It consists of a project work and a report.

HONOR SYSTEM: Honor system rules apply to all your work. It is your understanding that should be reflected in all work that you turn in. See http://ghs.grads.vt.edu/: “In working on projects and homework, discussion and cooperative learning on general topics is encouraged. Such discussion must be limited to general information such as lecture and text material. Using another student’s solution, design, implementation, or other specific results is strictly prohibited and is an honor code violation. Copying computer files or designs from any source is strictly prohibited and is an honor code violation. The midterm and final exams must be the work of the student. Consulting any other person except the instructor for this course about any aspect of an exam is strictly prohibited and is an honor code violation. Ask the instructor if you ever have a question about what is acceptable or unacceptable sharing.

” DISABILITY ACCOMODATION: Reasonable accommodations are available for students who have documentation of a disability from a qualified professional. Students should contact the Services for Students with Disabilities (SSD). Any student with accommodations through the SSD Office should contact me during the first two weeks of the semester.

RELIGIOUS ACCOMODATION: If participation in some part of this class conflicts with your observation of specific religious holidays during the semester, please contact me during the first two weeks of class to make alternative arrangements.

ACCOMODATION FOR MEDICAL OR PERSONAL/FAMILY EMERGENCIES: If you miss class due to illness, especially in the case of an exam or some deadline, contact a professional in Schiffert Health Center. If deemed appropriate, documentation of your illness will be sent to the Dean’s Office for distribution to me. If you experience a personal or family emergency that necessitates missing class, contact the Dean of Students at (540) 231 3787.

COURSE OUTLINE

1 - Estimation of location and Scale

   1.1 Estimators of location

   1.2 Estimators of scale

   1.3 Outlier identification methods

2 - Probability Distribution Theory

   2.1 The Gaussian distribution

   2.2 The Laplacian distribution

   2.3 The Cauchy distribution

   2.4 The Student distribution

   2.5 Mixture of probability distributions

3 - Parametric Estimation Theory

   3.1 Maximum Likelihood estimators

   3.2 Fisherian concept of consistency and efficiency

   3.3 Equivariance properties of an estimator

4 - M-estimators

   4.1 Definition

   4.2 Sub-classes of M-estimators

   4.3 Properties of the M-estimators 2

5 - Robustness concepts

   5.1 Qualitative robustness

   5.2 The breakdown point

   5.3 The influence function

6 - Regression estimators

   6.1 Simple regression

   6.2 Least squares estimator

   6.3 M-estimators

   6.4 Robust estimation of multivariate location and covariance

   6.5 Leverage point identification

   6.6 Generalized M-estimators

7 - Robust filters

   7.1 The auto-regressive model

   7.2 Least squares estimation of AR models

   7.3 Robust estimation of AR models

   7.4 Robust estimation of ARMA models

8 – Long-Memory and Self-Similar Processes

   8.1 Definitions

   8.2 Hurst coefficient estimation

   8.3 Estimation of fractional ARIMA models

9 - Kalman Filter

   9.1 The model

   9.2 Classical Kalman filter

   9.3 Robust Kalman filter

10 - High-Breakdown estimators

   10.1 Least Trimmed squares estimator

   10.2 Least median of squares

   10.3 The resampling method

11 - Applications

   11.1 Image processing

   11.2 Radar systems

   11.3 Internet data processing

   11.4 Power system state estimation and load forecasting

Alexandria: 1021 Prince St.
703.838.8320
kanacker@vt.edu

Course Description

This introductory course is designed to help students writing the first draft of their Major Paper or Practicum Report, one of the graduation requirements in Urban Affairs and Planning (UAP). Special emphasis will be placed on qualitative research methods, typically discussed in Chapter/Section 3 of a Major Paper or Practicum Report (or any scholarly publication).

Course Objectives

At the conclusion of this course, students should

• be able to formulate research hypotheses/questions/goals
• be able to develop surveys
• be able to draw samples
• be knowledgeable about the Institutional Review Board
• be knowledgeable about sources of research funding
• be able to write grant proposals
• be able to conduct short analyses
• be knowledgeable about sources of publishing

Class Website

This class uses Blackboard in order to enhance the online learning experience of students. This website contains a discussion board, a course calendar, and other pertinent information. Please go to https://learn.vt.edu.

Required Reading:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,: Sage Publications).

Course Requirements:

Class Attendance/Participation/Behavior

Students are required to attend class and to participate in discussions. Students are expected to arrive on time. Using cell phones (which includes sending or receiving text messages) is not allowed in this class.

Reading Assignments

Students are required to familiarize themselves with and understand the class readings before each class. Readings will be discussed during class time.

Writing Assignments/Final Paper

Students are required to submit several assignments over the course of the term, as specified below. These assignments will be returned to the students with comments the following week. Throughout the semester students are encouraged to submit drafts of their Major Paper/Practicum Report to the instructor. On November 20 or December 4 students will present their research projects to the UAP community (30-minute-presentation; 25% of grade) and submit their final papers to the instructor (15 pages minimum; 75% of grade). After the instructor returns the graded final paper students are expected to work with their advisor on subsequent drafts of their Major Paper/Practicum Report.

Final grades will be assigned based on the following scale:

A         95.00 points total – 100.00 points total

A-        90.00 points total – 94.99 points total

B+       85.00 points total – 89.99 points total

B         80.00 points total – 84.99 points total

B-        75.00 points total – 79.99 points total

C+       70.00 points total – 74.99 points total

C         65.00 points total – 69.99 points total

C-        60.00 points total – 64.99 points total

D+       55.00 points total – 59.99 points total

D         50.00 points total – 54.99 points total

F          below 49.99 points total

Assignment Submission, Late or Missing Assignments

The assignments must be submitted on paper or electronically via e-mail by the day they are due and by the beginning of class time (7:00 pm). An assignment that was handed in after 7:00 pm on the day it is due is considered late. Late assignments will not be commented on by the instructor.

Graduate Honor Code

The Graduate Honor Code establishes a standard of academic integrity. As such, this code demands a firm adherence to a set of values. In particular, the code is founded on the concept of honesty with respect to the intellectual efforts of oneself and others. Compliance with the Graduate Honor Code requires that all graduate students exercise honesty and ethical behavior in all their academic pursuits at Virginia Tech, whether these undertakings pertain to study, course work, research, extension, or teaching. A more detailed description of the University’s Graduate Honor Code may be obtained on the web at http://ghs.grads.vt.edu/student/index.html. More details on plagiarism and on how to avoid it may be obtained at http://ghs.grads.vt.edu/student/avoiding.html.

Disability Statement

If students need adaptations or accommodations because of a disability (learning disability, attention deficit disorder, psychological, physical, sensory issues, etc.), or if students have emergency medical information to share with the instructor, or if students need special arrangements in case the building must be evacuated, they should make an appointment with the instructor as soon as possible. If students need captioning for videos, they should let the instructor know no later than two weeks in advance of date on syllabus for viewing.

Course Schedule

August 28       Topic: Introduction to Class

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 3-30. (Chapter 1: Introduction to Educational    Research).

September 4   Topic: Introduction to Advanced Research Methods

                        Study Assignments for September 4^th:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 31-56, 251-288. (Chapter 2: Quantitative, Qualitative, and Mixed Research; Chapter 10: Validity of Research Results in

Quantitative, Qualitative, and Mixed Research).

 Writing Assignment (due September 11^th):            

Discuss the preliminary topic of your Major Paper/Practicum Report with your advisor. Free write [covered in class on September 4] about at least three research ideas for your Major Paper/Practicum Report and conclude your thoughts with “what I really mean is….”. 

September 11 Topic: Finding Research Gaps/Generating Research Ideas

                        and Conducting Literature Reviews

                        Study Assignments for September 11^th:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 59-88. (Chapter 3: Reviewing the Literature and Developing Research Questions).

 Writing Assignment (due September 18^th):

                        Find at least 20 publications that you will reference in your Major

                        Paper/Practicum Report. Write at least one page per publication for at least

five publications that you base your Major Paper/Practicum Report on. Answer the following questions:

                        * What research hypotheses/questions/goals are posed?

                        * What research methods are used? (elaborate!)

                        * What are the results?

                        * What are the stated limiations?

                        * What are the conclusions and policy implications?

                     
September 18 Topic: Formulating Research Hypotheses/Questions

                        Study Assignments for September 18^th:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 59-88. (Chapter 3: Reviewing the Literature and Developing Research Questions).

 Writing Assignment (due September 25^th):

                        Formulate at least three research hypotheses/questions of your Major

                        Paper/Practicum Report (these can be alternatives).

September 25 Topic: Selecting a Research Method

Study Assignments for September 25^th:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 355-419, 439-460, 291-354. (Chapter 13: Nonexperimental Quantitative Research; Chapter 14: Qualitative Research; Chapter 16: Mixed      Research; Chapter 11: Experimental Research; Chapter 12: Quasi-Experimental and Single-Case Design).

Writing Assignment (due October 2^nd):

                        Write at least one page about your research method and the justification

                        for selecting this particular research method.

October 2       Topic: Developing Surveys

                        Study Assignments for October 2^nd:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 199-220, 169-198. (Chapter 8: Methods of Data Collection; Chapter 7: How to Construct a Questionnaire).

Writing Assignment (due October 16^th):

                        Develop a survey (four typed pages maximum), possibly in Survey

                        Monkey.

October 9       [instructor at HERA conference in Indianapolis, IN]

October 16     Topic: Drawing Samples

Study Assignments for October 16^th:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 221-250. (Chapter 9: Sampling in Quantitative, Qualitative, and Mixed Research).

Karyn R. Lacy (2007) Blue-Chip Black: Race, Class and Status in the New Black Middle Class (Berkeley et al.: University of California Press) 227-234. (Appendix A: A Recipe for Studying the Black Middle Class). (available on Blackboard)

 Writing Assignment (due October 23^rd):

                        Discuss your sampling strategy, incorporating your strategy for non                                     responses.

October 23     Topic: Adhering to Research Ethics

Study Assignments for October 23^rd:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 99-132. (Chapter 5: Research Ethics).

 Writing Assignment (due October 30^th):

                        Complete the IRB paperwork for new studies.

http://www.irb.vt.edu/pages/training.htm#VTTutorial
http://www.irb.vt.edu/pages/newstudy.htm#ExeForm

Submit your IRB certificate to the instructor.

 
October 30     Topic: Finding Research Funding and Writing Grant Proposals

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 89-98. (Chapter 4: How to Write a Research Proposal).

 Writing Assignment (due November 6^th):

                        Find at least five potential sources of funding. Select the most promising

                        one and write a grant proposal to obtain funding for your Major

                        Paper/Practicum Report.

 November 6   Topic: Conducting Analyses

                        Study Assignments for November 6^th:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 463-558, 135-168. (Chapter 17: Descriptive Statistics; Chapter 18: Inferential Statistics; Chapter 19: Data Analysis in Qualitative and Mixed Research; Chapter 6: Standardized Measurement and Assessment).

 Assignment (due November 13^th):

                        Submit a draft of your presentation/discussion.                       

November 13 Topic: Disseminating/Publishing Research Findings

Study Assignments for November 13^th:

Burke Johnson & Larry Christensen (2008) Educational Research: Quantitative, Qualitative and Mixed Approaches (Los Angeles, CA et al.,:

Sage Publications). 561-580. (Chapter 20: Preparation of the Research Report).

November 20 Topic: Presentation/Discussion of Research Projects (part 1)

November 27 [no class – Thanksgiving Day]

December 4    Topic: Presentation/Discussion of Research Projects (part 2)

Email: mdull@vt.edu
Tel. 703-706-8117 (office) 202-821-3807 (cell)

Course Description

This class is about applying knowledge to the problems administrators and analysts encounter each day. What do I know? How confident am I? What do I need to know? Simple enough; but the answers are often complicated, uncertain, time-consuming, controversial, and – in ways that are sometimes almost invisible – fraught with opportunities for faulty inference. Our purpose this semester is to think carefully about the hazards of information and inference in order to improve how we bring knowledge to bear on pressing problems. The course has three basic objectives:

1) Examine problems of evidence and causation in social research of any kind, and in policy and public administration research in particular.
2) Build a common understanding of concepts in quantitative research methodology: variables and distributions, statistical significance, hypothesis testing, linear regression.
3) Prepare students for the creative, pragmatic application of information and analytical thinking to problems common in public policy and public administration.

Required Texts
The following texts will be required for all students taking the course. Please make arrangements to purchase both:
Elizabethann O’Sullivan, Gary Rassel, and Maureen Berner. 2006. Research Methods for Public Administration. Longman, 4th Edition. ISBN: 0321085582
*Note that this is the hardcover 4th Edition. Used copies are available online.
Wayne C. Booth, Gregory G. Colomb, Joseph M. Williams. 2008. The Craft of Research. University of Chicago, 3rd Edition (Paperback). ISBN: 0226065669.
Joel Best. 2001. Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists. University of California Press. ISBN: 0520219783.
Other course readings will be made available in electronic copy on Blackboard. Completion of an introductory statistics course is required for this course. It is also strongly recommended that you review a basic statistics text. One text that is clear and available used is:
Robert M. Kaplan, 1986. Basic Statistics for the Behavioral Sciences. Allyn and Bacon, Inc.

Course Contribution

Regular attendance and informed contributions to class are both a part of your grade and essential to learning. This requires: 1) Regular attendance; 2) Informed contributions based on a close reading of course materials; 3) Reading and offering feedback on other participants’ work; 4) Regularly posting research updates and drafts to the “Projects” discussion on Blackboard.

Problem Sets

Four problem sets applying material covered in class are due before class on the dates designated on the course schedule. Problem sets #1 and 2 are to be turned in to me in paper copy at the beginning of class; Problem Sets #3 and #4 should be submitted in electronic format via Blackboard. A full letter grade will be deducted for each day a problem set is late.

Paper Proposals

In one or two pages state clearly the question or problem motivating your paper. Identify how the information you will collect and interpret will contribute to existing knowledge. Why should readers be interested in our research? Why should readers deem your research credible?

Datagraphy – Numbers Paper

Identify and examine an interesting policy number. This number may be interesting because it is influential or because it serves as an indicator of a concept or relationship you deem important. In a concise 1500-word profile, consider:
Description – Identify the indicator. What concept does it operationalize? What are the underlying data, who collects it, and how often?
Distribution: If possible, include a trend or distribution representing the number. How, if at all, does representing the distribution inform how the indicator is interpreted?
Development – Where did the number come from and why? Have the underlying methodology, how the number is reported, or the number’s audience changed?
Why the number is interesting? – Explain why the indicator is interesting. What issues does it draw attention to – what issues might it obscure?

Here are a few datagraphy examples:
African-American voter turnout
Blood pressure
Bowl Championship Series (BCS)
Budget deficit
Carbon footprint
Consumer confidence
Credit score
Crime rate
Foreclosure rate
Gini coefficient
Gross Domestic Product (GDP)
Hospital quality indicators
Intelligence quotient
Literacy rates
Nielsen ratings
Olympics medal counts
Pages in the Federal Register
Poverty line
Presidential approval rating
S&P 500 Index
SAT scores
Size of government
Standards of Learning (SOLs)
Speed limit
Stagflation
Systeme International (SI) Time
U.S. News College Rankings

Final Paper: Research Design or Empirical Paper
We will discuss the format of the final paper in greater detail during the course of the semester. As a preliminary matter, your final paper should be a short (10-15 pages) research design or empirical paper. At a minimum your paper should include the following:
Problem Statement and Overview
Hypotheses or Expectations
Method of Data Collection
Scholarly or Policy Contribution

Email: yuewang@vt.edu
Phone: (703) 387-6056
Fax: (703) 528-5543

This course will cover supervised learning, pattern classification, neural networks, support vector machine, unsupervised learning, cluster analysis, feature discovery, cross-validation, and independent component analysis, with an emphasis on the strategic frontier between machine learning and scientific discoveries. The course is theoretical, practical, and challenging in nature. Major effort will be made to present applications in the areas of genomic bioinformatics, computational biology, biomedical imaging, and computer-aided decision making.

Lectures: Tuesdays, 4:00pm – 6:45pm (Blacksburg: check with official schedule)

Office Hours: Tuesdays, 6:45pm- 7:30pm (e-mails are greatly welcome)

Textbook: T Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, Springer, 2001.

References: Simon Haykin, Neural Networks: A Comprehensive Foundation, Prentice-Hall, Inc., 1999.
Hyvarinen, A., Karhunen, J. & Oja, E. Independent Component Analysis, John Wiley, New York, 2001.
Ripley, B. Pattern Recognition and Neural Networks, Cambridge University Press, 1996.

Pre-requisite: A graduate course covering probability theory, random variables, and random processes. Knowledge about signal detection and estimation is desirable (e.g., ECE 5605/5606).

Grading: Reading report 25%
Term paper proposal 25%
Final term paper 50%

Course Outline: Introduction to statistical and machine learning theory, statistical decision principles, linear discriminant analysis, Fisher criterion, multilayer perceptrons, support vector machine, feature selection, cross-validation and re-sampling, principal component analysis, self-organizing maps, mixture model and clustering, independent component analysis.

Honor Code: Adherence to Virginia Tech’s honor code is fully expected. Please discuss any questions you may have about what is or is not permitted with the instructor.

Educational Research Program, School of Education

office 703.538.8477
home 301.951.5291
e-mail: gbelli@vt.edu

TEXT

Czaja, R. & Blair, J. (2005) Designing Surveys: A Guide to Decisions and Procedures (2nd edition). Thousand Oaks, CA: Sage.

READINGS AND ELECTRONIC RESOURCES

Cobanoglu, C. Warde, B., & Moreo, P.J. (2001) A comparison of mail, fax, and web-based survey methods. International Journal of Market Research, 43(4), 441-452.
Griffis, S.E., Goldsby, T.J. & Cooper, M. (2003). Web-based and mail surveys: A comparison of response, data, and cost. Journal of Business Logistics, 24(2), 237-258.
Hutchinson, S.R. (2004) Survey Research. In K. deMarrais and S. D. Lapan (eds.) Foundation for research: Methods of inquiry in education and the social sciences (pp. 283-301). Hillsdale, NJ: Lawrence Erlbaum Associates.
Presser, S. and Blair, J. (1994). Survey pretesting: Do different methods produce different results? Sociological Methodology, 24, 73-104.
Trochim, W. M. The Research Methods Knowledge Base, 2nd Edition. Internet WWW page, at URL: <http://www.socialresearchmethods.net/kb/). (version current as of 10/20/06)
A web resource for statistical and research information. Sections to be used are:
• Survey Research Section
• Sampling Section
• Measurement Section
• Data Preparation

NOTE: Paperback version of text is available at a discount. If interested, ask me for code #.
Finding Published Instruments (http://www.apa.org/science/faq-findtests.html) A web guide for locating and using published and unpublished instruments: American Psychological Association, Science Directorate (2002), FAQ/Finding Information About Psychological Tests.
Boros Institute: Mental Measurements Yearbook Test Reviews Online
NOTE: Get to this via VT library page.

Optional readings:
DeVellis, R.F. (2003). Scale Development: Theory and Applications. Newbury Park: Sage.
Dillman, D. (2000). Mail and Internet Surveys: The Tailored Design Method (2nd ed.). NY: John Wiley & Sons.
Rea, L.M. and Parker R.A. (1997). Designing and Conducting Survey Research: A Comprehensive Guide (2nd ed.). San Francisco: Jossey-Bass.
Tourangeau, R., Rips, L., & Rasinski, K. (2000). The Psychology of Survey Response. Boston: Cambridge University Press.
Catalogue Description
This course provides an overview of survey research for graduate students in education. It covers the process from project formulation and sampling, through instrument design and question formulation, to data processing and report writing. Emphasis will be on questionnaire design, providing students with an opportunity to create and revise their own questionnaire and critique instruments used in educational surveys.
Additionally, published measures of different constructs will be found and examined.
Educational Objectives
The main objective of this course is to develop an understanding of the “soup to nuts” of survey research. After successfully completing this course, the students should be able to:
1. Explain the place and role of survey research within the broader arena of educational and behavioral science research.
2. Distinguish between different survey designs and sampling techniques.
3. Describe the strengths and weaknesses of different types of surveys.
4. Compare different methods of survey data collection in terms of advantages and disadvantages.
5. Design a simple questionnaire for a specific purpose.
6. Understand the use of focus group interviews as an aid to developing questionnaires.
7. Describe the difference between composing individual questions and creating item scales to measure constructs.
8. Locate and evaluate published instruments from web sources.
9. Locate and evaluate published instruments from text sources.
10. Plan for data analysis given a specific questionnaire and survey design.

Internet and Email Usage
To enhance the text, information about surveys and survey research is available on the Internet. Links to specific Web sites and class notes will be available on Blackboard (http://learn.vt.edu) as HTML or PDF files. If you do not have an e-mail address, you can get a Virginia Tech PID from the library. Blackboard uses your VT PID’s to communicate. If you do not use this for your email, please configure it so that messages are resent to your own mail program.
Please use the following conventions or your notes & documents might get lost.
•SENDING EMAIL – Put SURVEY in subject line.
•SENDING ATTACHMENTS – Send files using the following format for file names: SURVEY-your last name-descriptive name for file.doc

Course Organization
The course is organized with an introductory overview lesson and four topical sections. We will follow the sequence presented in the topic outline. The
general format for class sessions will be part lecture and part group work and/or informal presentations and group discussions.
MP3 files of class lectures and discussions will be uploaded to Blackboard the day after class.

Assignments & Grading

Assignments listed within each topic’s section are to be initiated after the first lesson in that section and presented/discussed in subsequent class
sessions. Section assignments must be written and prepared for class presentation & discussion. These assignments are mainly to be used as learning/practice exercises and for class discussion. Class participation is an important aspect of this course.
A major class project/paper will be due at the end of the semester, but will also include interim reports. Written feedback and grades will be assigned based on these reports. Informal project presentations will be made throughout the semester. The nature of these reports may vary across students and will depend on individual student needs and goals. Several options will be offered and the choice will be based on a mutually agreed outline of each individual project.
The VT Graduate Honor Code includes a discussion of plagiarism and how to avoid it. This is an important aspect of research writing and you will be honor bound to abide by this.

7054 Haycock Road, Room 202G
Falls Church, VA 22043
Phone: 703.538.8491  Fax: 703.538.8465
ahuebner@vt.edu

COURSE DESCRIPTION AND OBJECTIVES:

This course is designed to provide students with the opportunity to develop an understanding of the process of conducting qualitative research and the completion of a qualitative thesis proposal. The three primary objectives of this course are to prepare students to: (1) be competent consumers of qualitative research; (2) perform and interpret qualitative data analyses; and (3) produce quality qualitative research of their own.  To accomplish these objectives, students will be required to read from selected books and papers relating to the philosophy of science, family theory, MFT research designs and methods, family measurement instruments, outcome research in family therapy, and a variety of special issues related to diversity such as gender and ethnicity.  In addition to the readings, a number of projects are required to give students the opportunity to have "hands on" experience with reviewing published research, coding and analyzing data, and developing a scholarly research proposal.

REQUIRED TEXT AND READING LIST:

Creswell, J. (2007). Qualitative Inquiry & Research Design: Choosing Among Five Approaches (2^nd Edition). Thousand Oaks, CA: Sage Publications.
Sprenkle, D. H. & Piercy, F. P. (2005) (Eds.).  Research methods in family therapy (2^nd Edition).  New York: The Guilford Press.
Supplementary readings will be available from the Blackboard website for the course at http://learn.vt.edu 

RECOMMENDED TEXT:

American Psychological Association. (2001).  Publication Manual of the American Psychological Association. (5^th Rev. ed.). Washington, DC: Author.

REQUIREMENTS:

Your attendance and productive participation will be important aspects of the learning process. Therefore, you will need to read and be prepared to discuss and/or ask questions about the readings assigned each week.  If you cannot attend a class, please notify Dr. Huebner via e-mail.  Since class attendance is a key component of your learning, anyone who misses more than two classes for any reason will have their grade reduced one level (e.g. A to B).

ASSIGNMENTS:

NOTE: Unless prior arrangements have been made with the professor, your assignment grade will decrease 2 points for each day it is late.

1. Class Preparation and Participation (25 points). This includes having read materials prior to coming to class and contributing to class discussion.

2.  IRB certification (25 points)

Every student will complete the IRB training certification tutorial. This is required prior to submitting and actual IRB request.

To access the Virginia Tech Human Research Participant Protections Tutorial, complete the following steps:

1. Go to the Blackboard website

2. Sign in using your PID

3. Go to the "Courses" tab on top

4. Click on "Browse Course Catalog" at the bottom right

5. Type in "Virginia Tech Human Research Participant"

6. Click "Enroll"

If you are having difficulty accessing this tutorial, contact Brandi Evans, Administrative Assistant, at (540) 231-4606 or bmdilday@vt.edu.

Successful completion of the tutorial requires a score of 70% or higher on the quiz at the end of the tutorial. Blackboard will automatically alert the IRB office of tutorials completed successfully. The IRB office will send a certificate of completion to all with passing scores via electronic mail.

3. Qualitative Coding Assignment (50 points). Will be explained in class.

4.  Research Proposal (80 points) & Oral Presentation (20 points)

The research proposal process will be discussed during class. Different portions of the proposal are due throughout the semester. Feedback will be given.

 
Introduction
Problem and setting
Significance
Theoretical framework
Purpose of study
Research questions/hypotheses
Literature review
Topic outline categories
Cite 5-6 major works in each area

 Methods:

Participants
Procedure/strategy
Plan for Analyses

           
Oral Presentation:

Oral presentation of your proposal will take the form of a proposal meeting where the student’s committee meets with the student to identify strengths and weaknesses in the proposal and to brainstorm ways to correct flaws.  You will have 10-20 minutes to present your study and 10-20 minutes to get feedback.  Prepare a short handout (1 page) outlining your study to facilitate their being able to help you (this is required).  Your presentation should include a brief description of the problem and why your proposed study will be useful (2-3 minutes).  However, the primary focus should be on the methods you will use to reach your objectives. Your presentation, including the handout, will be graded for organization, clarity and completeness (20 points).

5.  Final Exam (100 pts)

This exam will be completed in class. 

 
NOTE:  Lateness will result in a reduction (up to 10%) in grade.  We encourage you to talk with your colleagues about research ideas, your thoughts about your proposals. Of course, final written projects will be a result of your own work.  You are also strongly encouraged to meet with me to discuss your ideas and ask questions as needed. All written assignments should be typed and completed in APA format to receive full credit. 

 
GRADES

Grades will be based on the quality of work on the above assignments and exams (total points = 300).

Grading scale:

A  =  95% - 100% (288-300 pts)       B- =  81% - 83%  (243-251 pts)

A- =  91% - 94%  (273-287 pts)        C+ = 78% - 80%  (234-242 pts)

B+ =  88% - 90%  (264-272 pts)       C  =  74% - 77%  (222-233 pts)

B  =  84% - 87%  (252-263 pts)        C- =  71% - 73%  (213-221 pts)

7054 Haycock Road, Room 202G
Falls Church, VA 22043
Phone: 703.538.8491  Fax: 703.538.8465
ahuebner@vt.edu

COURSE DESCRIPTION AND OBJECTIVES:

            This course is designed to provide students with the opportunity to develop a basic understanding of the research process, statistical data analyses, and the steps needed for successful completion of a quantitative thesis proposal.  The three primary objectives of this course are to prepare students to: (1) be proficient consumers of research literature, (2) produce quality research of their own, and (3) perform and interpret statistical data analyses as necessary for objectives 1 and 2.  To accomplish these objectives, students will be required to read from selected books and papers relating to the philosophy of science, family theory, research designs and methods, family measurement instruments, outcome research in family therapy, research ethics, and a variety of special issues such as gender and ethnicity.  In addition to the readings, a number of projects are required to give students the opportunity to have "hands on" experience with reviewing and critiquing published research, coding and analyzing data (SPSS), and developing a scholarly research proposal.

REQUIRED TEXT AND READING LIST:

Salkind, N. (2007). Statistics for People who Think They Hate Statistics (3^rd Edition). Thousand Oaks: Sage.

Sprenkle, D. H. & Piercy, F. P. (2005) (Eds.).  Research methods in family therapy (2^nd Edition).  New York: The Guilford Press.

White, J., & Klein, D. (2002). Family Theories (2^nd Edition). Thousand Oaks: Sage Publications.

Supplementary readings will be available from the Blackboard website for the course at http://learn.vt.edu 

RECOMMENDED TEXT:

American Psychological Association. (2001).  Publication Manual of the American Psychological Association. (Rev. ed.). Washington, DC: Author.

REQUIREMENTS:

            Your attendance and productive participation will be important aspects of the learning process. Therefore, you will need to read and be prepared to discuss and/or ask questions about the readings assigned each week.  If you cannot attend a class, please notify Dr. Huebner via e-mail.  Because class attendance is a key component of your learning, anyone who misses more than two classes for any reason will have their grade reduced ½ level (e.g. A to A-).

ASSIGNMENTS (Fall 2008):

NOTE: Unless prior arrangements have been made with the professor, your assignment grade will decrease 2 points for each day it is late.

 1. Class Preparation and Participation (25 points)

Every student will have read assigned reading material and contribute to class discussions.

 2.  Article Critique (50 points)

Every student will complete a critique of 1 quantitative research article (3-4 pages).  The article students will review will be available on the Blackboard website. The specific process and criteria for the critique will be discussed in class prior to the due date.  The critique is worth 30 points.  Critique due November 6.

 3.  Research Proposal (100 points) & Oral Presentation (25 points)

The research proposal process will be discussed during class. Different portions of the proposal can be submitted for feedback on the dates listed below. This is not required but is highly recommended. The final proposal is due Dec 4.

 Statement of the problem (due Oct 9)

 Overview of literature (9-10 major works in the area)

 Theoretical framework

Design: (Due Oct 30)

Sampling

Measures

Nov 13 & Nov 20:  Oral presentation of your proposal will take the form of a proposal meeting where the student’s committee meets with the student to identify strengths and weaknesses in the proposal and to brainstorm ways to correct flaws.  You will have 10-20 minutes to present your study and 10-20 minutes to get feedback.  Prepare a short handout (1 page) outlining your study to facilitate their being able to help you (this is required).  Your presentation should include a brief description of the problem and why your proposed study will be useful (2-3 minutes).  However, the primary focus should be on the methods you will use to reach your objectives. Your presentation, including the handout, will be graded for organization, clarity and completeness.

5.  Final exam (100 pts)

This exam will be completed in class on Dec 4. 

NOTE:  We encourage you to talk with your colleagues about research ideas, your thoughts about article critiques and your proposals. Of course, final written projects will be a result of your own work.  You are also strongly encouraged to meet with me to discuss your ideas and ask questions as needed.  Exams will be without the aide of books or friends.  All written assignments should be typed to receive full credit. 

GRADES

Grades will be based on the quality of work on the above assignments and exams (total points = 300).

Grading scale:

A  =  95% - 100% (288-300 pts)       B- =  81% - 83%  (243-251 pts)

A- =  91% - 94%  (273-287 pts)        C+ = 78% - 80%  (234-242 pts)

B+ =  88% - 90%  (264-272 pts)       C  =  74% - 77%  (222-233 pts)

B  =  84% - 87%  (252-263 pts)        C- =  71% - 73%  (213-221 pts)

The purpose for the panel discussions was to demonstrate some of the breadth of qualitative research.  Five VT faculty and one doctoral student from different disciplines provided their perspectives via brief overviews of their use of qualitative techniques in their research.
MP3 files are available for each presentation and for the two Q&A discussion sessions.
Links to slides or handouts are available for some presentations.

Click on presenter’s name for MP3 file.  

• Q1- Dr. Beverly Bunch-Lyons, History; oral histories
  Bootlegging and Juke Joint Culture
• Q2 - Dr. Rosary Lalik, Literacy Studies; auto-ethnography
  Notes on One Particular Qualitative Research Project (slides)
• Q3 - Dr. Hazhir Rahmandad, Industrial and Systems Engineering; grounded theory
  Qualitative Methods to Inform Building Simulation Models (slides)
• Q4 - discussion of Q1, Q2, Q3 presentations
• Q5 - Dr. Paul Renard, Adult Learning; historical research
  Historical Research Methods (handout)
• Q6 - Dr. Barbara Allen, Science and Technology in Society; ethnography and case studies
  Ethnography from the Inside Out: Researching Environmental Activism in Cancer Alley and Beyond
• Q7 - Ms. Annette Miles, Adult Learning; phenomenology
  Finding place in a “neurotypical” society:  A phenomenological study of individuals with Asperger’s syndrome
• Q8 - discussion of Q5, Q56, Q7 presentations

VT survey tool survey.vt.edu
Free for faculty and students. OK for short questionnaires where don’t need page-breaks or skip routines.

Blackboard learn.vt.edu - but this only works for VT PIDs

VT SONA system http://www.psyc.vt.edu/research/sona.html  - used by the Psychology Dept. for for online research study participation.

Leveson, N. G. (1995). Safeware: System Safety and Computers. Reading, MA: Addison-Wesley.

I teach this topic as it relates to software in CS5744 and CS6704.

We have a workshop series on software reuse and safety at ICSR.

See the website located at http://www.nvc.vt.edu/rmajor/bit5404

SMILE (Structural Modeling, Inference, and Learning Engine) is a fully portable library of C++ classes implementing graphical decision-theoretic methods, such as Bayesian net-works and influence diagrams, directly amenable to inclusion in intelligent systems. Its Windows user interface, GeNIe is a versatile and user-friendly development environment for graphical decision-theoretic models. Both modules, developed at the Decision Systems Laboratory, University of Pittsburgh, have been made available to the community in July 1998 and have now several thousand users worldwide.

http://www.arc.vt.edu/arc/sgi/index.php 

There’s info there about how to request an account. To use System X (a distributed memory cluster) means having an MPI-To develop one, a very simple description of what he wants to do can be uploaded at :

http://www.arc.vt.edu/arc/SystemX/index.php

Requests for these resources are reviewed by Prof. Cal Ribbens, CS Blacksburg.

and here are style and diction for Windows

http://www.akki-n.de/development/diction-and-style-for-windows

and here is a study using these tools

http://www.macnewsworld.com/story/35130.html?welcome=1202556583

Brad Shapiro, GTA, will be available  via polycom starting Monday, February 11th.  Appointments will be available on Mondays and Thursdays from 6:00-8:00 PM for 30 minutes to 1 hour.  All writing sessions will be held live via polycom at the Northern Virginia Center.

Location: Northern Virginia Center, Room 320, except on  2/28, 3/20, 4/24  Room  401
Days : Mondays and Thursdays
Time: 6:00-8:00

You may contact Brad for an appointment by email at bshapiro@vt.edu

Main points: Given the small size of each program and the growing interest in interdisciplinary work across funding agencies and scholarly circles, there is great need and value in pooling together the VT resources in the Northern Virgina for different collaborative activities. This committee will work on creating a structure to facilitate interaction between different departments that can lead to a better collegial environment for faculty and graduate students and more collaborative research. The following general areas were identified for facilitating collaboration:

• Seminar series
• Research collaborations
• Sharing courses
• Social activities

Current active seminars in the area include:

• ARI bi-weekly Bio seminar
• Occasional infrastructure seminars by Fred Krimgold
• CEE weekly seminars 3:30-5pm on Fridays (broadcast from Blacksburg)
• CS seminar series, 2-3 per semester o ISE/CEE seminar, supposed to be weekly, but in practice more like monthly, usually Friday afternoons

by D.R. Helsel and R.M. Hirsch
U.S. Geological Survey, Techniques of Water-Resources Investigations
Book 4, Chapter A3
Published in September 2002
This report is freely available only and is not for sale.
 http://water.usgs.gov/pubs/twri/twri4a3/

List of Appendix Data Sets in Excel spreadsheet.

This 510 page text is recommended by Dr. Tom Grizzard.

http://www.aaup.org/AAUP/pubsres/academe/