Located in 519 Baldy Hall, the Quantitative and Qualitative Data Analysis Lab (QQDAL) offers free assistance with issues related to quantitative and qualitative research design, data analysis and measurement/classification. The following software packages are housed in the lab: Atlas.ti, HLM, HyperResearch, LISREL, MPlus, nVivo, R, SAS, SPSS, Stata and Winsteps. Graduate assistants are available for consultation on the use of these packages.
Students, faculty and staff within the Graduate School of Education seeking help with course assignments and research projects are encouraged to make use of the lab.
No appointment is necessary during walk-in hours. Graduate lab assistants may also be available by appointment (contact us via email below). Consultations are available during lab hours either in person or via Zoom. Contact the relevant graduate assistant to schedule a time to meet.
| QQDAL Office Phone | Lab Directors | Lab Assistants |
|---|---|---|
716-645-4052
| Jaekyung Lee jl224@buffalo.edu Lois Weis weis@buffalo.edu | Quantitative: Preston Martin pmartin6@buffalo.edu Qualitative: Iman Lathan imanlath@buffalo.edu |
| Day | QUANTITATIVE LAB Preston Martin | QUALITATIVE LAB Iman Lathan |
|---|---|---|
| Tuesday | · | 11 a.m. – 4 p.m. |
| Wednesday | 9 a.m. – 2 p.m. | · |
| Thursday | 9 a.m. – 2 p.m. | 10 a.m. – 3 p.m. |
QQDAL is closed on all days that UB classes are not in session.
The following are topics that are often covered:
If you are seeking advice on writing a dissertation or master's thesis, please coordinate your work in the lab with your supervising faculty.
Do you have questions about the data analysis or research process with regard to quantitative research? Look below for a collection of useful resources for University at Buffalo students.
Statistical Formulas
Existing Surveys/Instruments
Sample Size Calculation and Power Analysis
Types of Analysis
Other Topics
Data Analysis/Management Software
| Locations | SPSS | SAS | R | HLM** | Multivariance | ArcGIS | AM |
|---|---|---|---|---|---|---|---|
| Capen 1st floor Cybrary | X | X | |||||
| Capen 3rd floor Cybrary | X | X | |||||
| Lockwood 2nd floor Cybrary | X | X | |||||
| Lockwood 3rd floor Cybrary | X | X | X | X | |||
| Baldy 14a* | X | ||||||
| Remotely via UB Virtual Computing Lab | X | X | |||||
| Remotely via UBUnix | X | X |
* GSE Lab Classrooms — not open for public use. All GSE graduate students may request access.
** Student edition
Data Analysis Software Tutorials
APA (American Psychological Association) Style Guide:
Managing References:
Consultations are available during lab hours either face-to-face or virtually via Webex. Contact the relevant graduate assistant to schedule a time to meet.
The following are topics that are often covered:
As per AERA (American Educational Research Association) standards, the statement of the problem must “provide a clear statement of the purpose and scope of the study” (Standards for Reporting on Empirical Social Science Research in AERA Publications, Educational Researcher, 2006, p. 34), make clear the theoretical underpinnings of the study, include a review of relevant scholarly literature, and include a rationale for the population or populations of interest.
The design of the study follows logically from the description of the research problem. Even within the broad category “qualitative investigation,” purposes and designs differ markedly, in accordance with the research problem. Whatever the design, it must be clearly and logically articulated from beginning to end.
Data are collected in accordance with the design of the study. Investigators need to make clear the research process so that later investigators can engage follow-up studies and multi-site investigations. Data collection techniques include: participant observation, observational inventories, structured or semi-structured interviews, focus group interviews, collection of artifacts, among others. In all cases, the ways in which data were collected must be carefully described, “including how and when they were gathered, by whom, and for what purpose” (Educational Researcher, 2006, p. 35).
Classification schemata should be clearly described, including how they were arrived at and how they were used to code data. When reporting out a classificatory scheme, concrete examples of data that support codes should be provided.
The purpose of analysis is to come to conclusions, on the basis of evidence, about the data at hand. All analytic techniques should be explained in notable detail and evidence for each claim should be described. Investigators should pay attention to data that do not support otherwise warranted claims — in other words, investigators should pay attention to disconfirming evidence and report these data out, as relevant.
The lab assistant can provide guidance on using qualitative data analysis software packages, for example, HyperRESEARCH and ATLAS.ti, to analyze data. With data analysis software, a researcher can code and run analyses on large amounts of data, aiding in the analysis, interpretation and writing up of the findings.
Do you have questions about the data analysis or research process with regard to qualitative research? Look below for a collection of useful resources for University at Buffalo students.
American Educational Research Association. (2006). Standards for reporting on empirical social science research in AERA publications. Educational Researcher, 35(6), 33-40. https://doi.org/10.3102/0013189X035006033
Bogdan, R. S., & Biklen, S. K. (2007). Qualitative research for education: An introduction to theories and methods (5th ed.). Boston, MA: Pearson A & B.
Glesne, C. (2011). Becoming qualitative researchers: An introduction (4th ed.). Boston, MA: Pearson.
Emerson, R. M., Fretz, R. I., & Shaw, L. L. (2011). Writing ethnographic fieldnotes. Chicago, IL: University of Chicago Press.
Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). San Francisco, CA: Jossey-Bass.
Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Thousand Oaks, CA: Sage Publications, Inc.
Data Analysis/Management Software
ATLAS.ti, HyperRESEARCH, and NVivo are installed in the QQDAL. Other analysis/management packages include: Dedoose (a cloud-based service, available at www.dedoose.com); MAXQDA.
Below is the student license cost for each software package. These prices are current as of July 2019. Please click on the software title for the most recent student license prices.
ATLAS.ti
License type - ATLAS.TI PC + MAC; License Cost - $99/$51; License Length - 2 years/6 months
HyperRESEARCH
License type - HyperResearch; License Cost - $199; License Length - Perpetual
NVivo
License type - NVivo 12 Pro; License Cost - $99; License Length - 2 years
Data Analysis Software Tutorials
ATLAS.ti Video Tutorials – ATLAS.ti offers introductory video tutorials on the overview of the software and how to get started with ATLAS.ti.
ATLAS.ti Team Collaboration – “This video shows how to structure a project for collaboration. It also describes the merging process.”
HyperRESEARCH Tutorials – HyperRESEARCH offers tutorials on working with various forms of data, including texts, graphic, video and audio.
NVivo Trial Resource Center – NVivo presents webinars, tutorials and blogs to help users learn how to use this software for qualitative data analysis.
Merit Library, University of Wisconsin-Madison: QDA Tools – Resources and tips on choosing and using software for qualitative research. Covers: ATLAS.ti, NVivo, MAXQDA, Dedoose.
University of Surrey: Choosing a Computer Assisted Qualitative Data Analysi Support (CAQDAS) – An overview of common functions of CAQDAS packages. Detailed reviews of ATLAS.ti, HyperRESEARCH, Dedoose, NVivo, MAXQDA and several other CAQDAS packages.
New York University: Qualitative Data Analysis: ATLAS.ti – NYU presents an introduction to ATLAS.ti; transferring data from ATLAS.ti 7 to ATLAS.ti 8; and setting up team projects.
The University of Illinois at Urbana-Champaign: ATLAS.ti – This tutorial focuses on the overview of ATLAS.ti, coding, generating queries and analyzing survey data.
The University of British Columbia, UBC Research Commons: NVivo – UBC organizes workshops on getting started with NVivo. They post tutorials on both MAC and PC.
Resources for Qualitative Research Methods
QualPage – Managed by Professor Kathy Roulston at the University of Georgia. QualPage collects resources about qualitative research. The website gathers a variety of information including but not limited to: ethics and qualitative research, qualitative research design, qualitative data analysis and writing up qualitative research. It also lists digital tools for transcription, data analysis and concept mapping.
International Institute for Qualitative Methodology, University of Alberta: Master Class Webinar Series – “The Qualitative Methods Master Class Webinar Series is an online colloquium on doing and using qualitative research. Connect to participate in presentations from internationally renowned qualitative researchers – learn about the latest innovations in methods and exchange ideas about your research with researchers from all over the world.”
The Qualitative Research Special Interest Group (SIG) of AERA: Qualitative Conversations – This series of podcasts invites scholars to talk about their qualitative works.
University of Wisconsin-Madison: Quarterly Workshops and Online Lecture Series: – Institute for Clinical and Translational Research at UW-Madison presents quarterly workshops on qualitative and mixed methods research. Videos of these workshops are available online, covering topics such as an overview of qualitative research methods, focus groups, qualitative data analysis, and writing and publishing qualitative research.
Robert Wood Johnson Foundation: The Qualitative Research Guidelines Project – This website was developed as a guideline project for researchers developing, evaluating and engaging in qualitative research projects in healthcare settings. The guidelines introduce a wide range of qualitative research methods and analytic approaches, and identifies criteria for evaluation.
Resources for Transcription
UCLA: Resources for Transcription – UCLA gathers publications, tutorials and software on transcribing qualitative data.
University of Manchester: Toolkit 08: Transcribing Your Own Qualitative Data – This toolkit advises on how to plan properly for transcribing qualitative data. It provides an EXCEL calculator to estimate transcribing time.
UK Data Service: Transcription – This webpage offers tips on generating transcripts of good quality, and planning format/template for transcription.
Resources for Coding and Analysis
University of Surrey: Team Working Using CAQDAS Packages – This webpage gives advice on collaboration in qualitative research with the assistance of CAQDAS packages. It presents general protocols for data collection, analysis and data outputs in group qualitative projects.
Resources for Archived Qualitative Data
Corti, L., Fielding, N., & Bishop, L. 2016. Editorial for Special Edition, Digital Representations: Re-using and Publishing Digital Qualitative Data. SAGE Open, 6(4): 1-3. https://doi.org/10.1177/2158244016678911
Syracuse University: Qualitative Data Repository (QDR) – “QDR curates, stores, preserves, publishes, and enables the download of digital data generated through qualitative and multi-method research in the social sciences. The repository develops and disseminates guidance for managing, sharing, citing, and reusing qualitative data, and contributes to the generation of common standards for doing so.”
UK Data Service: Qualitative/Mixed Methods Key Data – UK Data Service provides fully anonymized quantitative, qualitative and mixed methods data.
APA (American Psychological Association) Style Guide:
Managing References:
If you are seeking advice on writing a dissertation or master's thesis, please coordinate your work in the lab with your supervising faculty. You should additionally make use of the Center for Excellence in Writing, 209 Baldy Hall, when writing a dissertation or master's thesis. You need to make appointments directly with individuals in the center. Be sure to plan ahead to have enough lead-time to complete your work.
