Research Statisticians
- Dr. Larissa B: Industrial-Organizational Psychology, Research Methodology, Psychology, Criminology, Criminal Justice, Business, Education.
Research Methodology: Identifying levels of measurement, choosing a statistic for your research question, developing testable hypotheses/operationalizing variables, survey design and instrumentation (includes web-based/online), experimental and applied research design, program evaluation, psychological/educational tests and measures.
Data Analysis and Interpretation: descriptive statistics, assumption testing, reliability, t-tests, correlation and regression, chi-square, ANOVA/ANCOVA (one-way, two-way/factorial, repeated measures), MANOVA/MANCOVA, discriminant function analysis, path analysis, factor analysis, structural equation modeling
Statistical Reporting: scholarly (APA style) and applied (client-friendly) statistical reporting, including tables/graphs
Statistical Programs: SPSS, AMOS, MiniTab
Microsoft Office Programs: Excel, Word, PowerPoint
- Victoria Briones: Organizational Psychology, Statistics: (SEM; using AMOS, LISREL, and EQS). Victoria helps graduate students in psychology, education, nursing, biology, and business hone their study hypotheses, arrive at better operational definitions of their study variables, and improve procedures to increase the internal and/or external validity of their study. She also performed general statistical procedures such as reliability analyses, non-parametric tests (e.g., Mann-Whitney, Kruskal-Wallis, and chi-square tests), t-tests, analysis of variance (ANOVA), analysis of covariance (ANCOVA), exploratory factor analysis (EFA), and linear regression. Further, she conducted multivariate tests such as multivariate analysis of variance (MANOVA), logistic regression, and structural equation modeling (SEM; using AMOS, LISREL, and EQS). Victoria also created summary tables and graphs of statistical findings and helped students interpret their study results. More importantly, she enjoyed explaining basic statistical procedures and findings to clients who had a limited understanding of such concepts.
- Lynetta Campbell: Mathematics, Management Science, Chemical Engineering, SAS, SPSS, JMP, and R statistical software. olds an M.S. in Mathematics, an M.S. in Management Science, a B.S. in Chemical Engineering. She assists graduate students their initial exploratory data analysis, usually with a graphical approach to viewing the data. She makes sure each client understands the basics, such as how to properly state the null and alternative hypotheses, and how to test for equivalence using procedures such as independent sample or paired sample t-tests. She routinely helps clients in the selection of the proper regression methods to employ, helping them to understand generalized linear models, logistic regression, and logit and loglinear models. Her ultimate goal is always that the client gains a full understanding of what the data has to say. In this manner, she has worked with clients whose data was highly qualitative, such as survey data, and she has assisted students with highly quantitative data involving modeling and forecasting.
- Emil Freeman: Data Analyst - Research Statistician, JMP Consultant, Polymer Science, Chemical Engineering.
- Tom Granoff: Data Processing, Research Methods and Data Analysis--Psychology, Counseling, Education, Public Health, Leadership, Business, Marketing, Sociology, Management, Nursing, Theology, Industrial Psychology.
- Elizabeth L. Pearman: Survey Design, Data Analysis and Programming ( SAS and SPSS), Assessments, Research Design, Research Mthods, Educational Psychology
- Jane Scott: Personality Psychology, Statistics, Research Methods, SAS, SPSS, Mathematics.