Quantitative data analysis appointments allow doctoral students working on their project study or dissertation to have one-on-one sessions with a quantitative methodologist. Students may ask any questions pertaining to data analysis. The quantitative methodologists provide assistance in data analysis, SPSS or interpretation of results for reporting purposes.
If you have questions concerning research (RSCH) course concepts or assignments, please contact the Academic Skills Center for course tutoring: https://academicguides.waldenu.edu/academic-skills-center/tutors
Appointments are held in Zoom. Weekly slots are limited. Please make only one appointment a week so that other students also have a chance to make timely appointments. If you need more than one appointment, you are welcome to make one for another week.
SPSS is a software package that provides students with statistical analysis, modeling, predictive, and survey research tools used in many of our courses and advanced research activities. Walden is pleased to be able to offer this important resource free of charge for the duration of your program.
If you are currently using SPSS software supplied by Walden University, you will need to enter an updated access code on or before March 31, 2023. As of March 31, 2023, your existing license will expire and you will not be able to use the program. Click here to read the instructions for updating an expired license. The codes will be valid until March 31, 2023.
Walden is pleased to offer SPSS version 28 this year. SPSS version 28 is supported on the following operating systems:
If you are using a previous version of SPSS, it is recommended that you upgrade to v. 28. Please refer to the install guides for your operating system. You may need to uninstall the older version prior to installing v. 28.
If you have any questions about this change or need assistance downloading SPSS, please contact Walden’s Customer Care Team from your myWalden portal by choosing the Support tab and clicking “Click to Chat.” You can also call 1-800-WALDENU (925-3368). Please include your name, student ID number, and degree program with any correspondence.
Dr. Ozcan have been involved with education at multiple levels, throughout K-12 and higher education, teaching classes and leading various research projects. After receiving her Ph.D. from The University of Texas at Austin, Dr. Ozcan have taught research methodology courses and conducted assessment and program evaluation studies with higher education institutions as well as school districts and various state agencies. She serves as a statistics tutor at the Office of Research and Doctoral Services.
Dr. Taylor started with Walden in 2007 in the School of Psychology as a contributing faculty. He transitioned to the Doctor of Business Administration program in 2013 as a Program Coordinator. Dr. Taylor joined the Office of Research and Doctoral Services in 2019. In his role in ORDS, Reggie provides methodology and statistics support, one-on-one statistics and SPSS tutoring support. He is also responsible for expanding these tutoring and methods advising services to address broader student research support needs at the doctoral capstone stage.
Dr. Liu has taught research methods and statistics courses for several years. Her research interests include longitudinal data analysis, secondary data, and advanced statistical modeling. She serves as a statistics tutor at the Office of Research and Doctoral Services.
Zin Htway, PhD, MBA, teaches or has taught statistical methods in computational biology; advanced immunology; epidemiology and environment; cancer and society; sex, germs, and diseases; and quantitative methods for biology. Dr. Htway has worked as a researcher in community-based research settings in a variety of areas, including avian influenza detection and diabetes among Hispanic populations, and has served as principle investigator or methodology/statistics expert in many of those projects. Dr. Htway earned his PhD in public health and epidemiology from Walden University in Minneapolis, Minnesota.