Dr. Victoria Briones graduated with a Ph.D. in Organizational Psychology from Columbia University. While completing her graduate studies, she taught applied regression analysis to graduate students in education and psychology. Students enjoyed her regression course because she was able to translate complex statistical concepts into a language that the “stats phobic” students could easily understand. Victoria was also an assistant lecturer in research methods (and received the highest mean evaluation for teaching performance). After graduating, she was a research vellow at Harvard University's Kennedy School of Government. As a fellow, she conducted statistical analyses and wrote articles on negotiation behavior and conflict resolution with her former dissertation adviser.

In the last two years, Victoria has worked as a statistical consultant, helping 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.

Scope: research methods, reliability analyses, t-tests, ANOVA, repeated-measures ANOVA, ANCOVA, exploratory and confirmatory factor analyses, multiple linear regression, logistic regression, MANOVA, structural equation modeling (AMOS, LISREL, and EQS)

Additional information

Lynetta Campbell holds an M.S. in Mathematics, an M.S. in Management Science, a B.S. in Chemical Engineering. 

Ms. Campbell worked twelve years in the Chemical Process Industry, during which time she participated in the design, construction, and start-up of projects in polystyrenics. However, it was her work in the implementation of statistical quality control programs that lead her to focus on data collection and analysis.

Ms. Campbell teaches mathematics and statistics.  Her students write that “she explains things clearly and does not make anyone feel stupid for asking questions.”  She is a CRLA-certified tutor who takes great pride in helping students come to “own” the mathematical knowledge necessary to succeed in their chosen fields. 

She has assisted graduate students with their data analysis in fields as diverse as engineering, education, and public health.  She can assist clients with 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.  She is highly proficient with SAS, SPSS, JMP, and R statistical software and programming languages..

Additional Information

Dr. Emil Freeman is an experienced statistician and polymer scientist/engineer. As an internal consultant for a major rubber company he helped many associates solve R&D and quality assurance problems by identifying their root cause. As a statistician in the pharmaceutical industry he analyzed stability studies to predict shelf lives, designed and analyzed studies of biological, chemical and manufacturing processes, and solved problems for quality control statisticians faced with "unusual situations". His independent consulting assignments have covered a wide range: promotional games, tire life studies, agricultural experiments, electronic signals. He is an expert at designing experiments to fit each customer's needs: fractional factorials, composite designs, incomplete block designs, Youden Squares, etc. He is an expert in Multiple Criteria Optimization and analyzing "messy data" (multiple error terms, mixed models, components of variation, regression, ANOVA, ANOCOVA). He is an expert user of JMP software, and was a beta-tester and contract JMP instructor for the SAS Institute.

He has mentored and tutored a wide range of individuals, from children and adolescents with learning disabilities to non-statistician scientists and engineers. He loves to hear the magic words, "This isn't as hard as I thought it would be."

He has published eight peer-reviewed papers and has four US patents. He holds a BS from MIT, a PhD and MA from Princeton University, and an MS from Case Western Reserve University.

Appraisals said, "...recognized and much-sought internal consultant and expert in statistical methods and their application to real problem solving.... Excellent listener and dissector of the key needs/wishes of his customers.... Focuses their work to answer their desired questions, and creates experimental approaches specific to each problem."

Note: All analyses performed with JMP.

Additional information

Tom Granoff, Ph.D., has spent almost 30 years providing research methodological and data analysis support in academic settings using SPSS and SAS. Tom typically works on numerous scholarly projects each year. Tom assists students who are obtaining advanced degrees in psychology, counseling, education, public health, leadership, business, marketing, sociology, management, and nursing. He also worked for many years in marketing research and data processing positions in the health care industry. A popular instructor, Dr. Granoff teaches graduate-level research methods and statistics courses for Loyola Marymount University and Pepperdine University, both in Los Angeles. He prides himself in being able to explain most multivariate statistical tests in simple English without using complex mathematical formulas. Tom educates his clients so that they car take full responsibility for the contents of their study, and assists them in preparing for their oral defense.  His formal education includes a Ph.D. in Clinical Psychology plus Master's degrees in Theology and Industrial/Organizational Psychology.
For research proposals (Methods Chapter), Tom provides technical assistance in the following ways: helping set up the research design, reviewing surveys, assistance in selecting appropriate statistical tests, helping determine needed sample sizes (power analyses), helping develop operational definitions; developing hypotheses/research questions; measuring constructs; and tutoring students in the understanding and usage of appropriate research and statistical terminology.  Tom often edits the Methodology Chapter to ensure that the purpose statement, research questions, the hypotheses, the data gathered, and the statistical approaches are in accord.  
For data analysis projects (Results Chapter), Tom’s provides ethical assistance that does not conflict with your university’s plagiarism and academic integrity policies.  Tom will first have a brief free consultation with the student’s thesis/dissertation advisor and gain the appropriate permission before any formal work is conducted.  After securing written permission, Tom can provide any of the following services: create suitable SPSS files, help prepare the dataset for analysis, run relevant statistical tests or teach the student how to do it themselves, provide tutoring in the interpretation of SPSS output, and provide generic examples of how SPSS output could be transformed into APA style tables and narrative.  After the student has the draft of the Results Chapter, Tom can then provide technical editing to ensure the findings are presented in a clear, accurate and compelling manner.

See additional feedback

Articles (1) Preparing for Your Oral Defense (2) Myths and Truths About Academic Research Projects

Ronald B. Marks, PhD was a marketing professor, now retired from the University of Wisconsin. He received his Ph.D. from the University of Missouri - Columbia, with a major in Marketing and minor in statistics. During his thirty year career, he taught undergraduate and graduate market research and multivariate statistics amongst other courses. He made extensive usage of SPSS, Minitab, and LISREL in both teaching and research. His research credentials in the use of multivariate statistics are evidenced in articles, such as: "A Structural Equation Model of Predictors for Effective Online Learning," Journal of Management Education, 29 (4), August, 2005 and "Psychometric Evaluation of the ADAPTS Scale," Journal of Personal Selling and Sales Management, Vol. XVI (4) (Fall, 1996, 53-56)

He attended seminars in "Multivariate Statistics" at the University of Colorado and "General Structural Equation ("Lisrel") Models," (Introduction and Advanced) at the Inter University Consortium for Political and Social Research, University of Michigan, Ann Arbor. He also conducted similar faculty seminars in Multivariate Statistics at the University of Wisconsin.

In counseling dissertation students and business clients, his experience is that "a problem well defined is half solved." Or as Tom Peters suggested in his best-selling book on management, "if you don't know where you are going, you are likely to end up somewhere else." That is, no matter how arcane the statistics employed, they will never compensate for poorly stated hypotheses and literature review. Hence, when consulting with students, he helps them first develop lucid, operational hypotheses and then determines which statistical methods to use, rather than the converse.

Scope: multivariate statistics, behavioral sciences, marketing research, research design, SPSS, Minitab, structural equation modeling (LISREL), survey research, web-based surveys, quantitative methods, correlation, ANOVA, MANOVA, multiple regression, discriminant analysis, factor analysis, methodology chapter editing, nonparametric tests (such as chi-square or Mann-Whitney U Test), statistical application to social science data (e.g. psychology, sociology, economics) and business data (e.g. finance, business, and marketing), can aid with set-up of data files, analysis of sample characteristics, can also help develop persuasive Power Point presentations for oral defenses or business presentations.

Additional information

Raymond D. Mooring, Ph.D. has spent nearly a decade studying, teaching, and analyzing statistics.  He received a Ph.D. in Atmospheric Science with a concentration in Statistical Climatology from Georgia Institute of Technology. 

While working for the US Department of Treasury as a Statistician, Ray has authored or co-authored over 25 sensitive, but unclassified technical reports.  In this capacity, he conducted data analysis for research teams, provided assistance to other analysts when initiating, planning, implementing, controlling, modifying, and executing all parts of a research project, and reviewed and analyzed all material produced for studies for reasonableness and accuracy. 

Ray has taught statistics to undergraduate business majors and graduate MBA students.  He currently teaches statistics to non-Math majors. In addition, Ray has provided statistical support to students in diverse fields such as climatology, mechanical engineering, electrical engineering, chemistry, education, finance, biology, and even ministry.   

Ray can help clients demystify statistics.  Regardless if you need help in conceptualizing the methodology section of your dissertation, setting up your experiments, analyzing your results, interpret your results, or proving or disproving your company's hypothesis, Ray will be able to provide you with accurate answers that are easy to understand and actionable.  

Finally, Ray takes pride in teaching others statistics.  As a result, he will teach short statistics courses to your department or company.  If you do not have a training budget for your employees, providing a short course is an economical way to train several employees in the fundamentals and applications of statistics.  Short course notes may also be provided if you like.

Scope:
Science — Statistical Analysis, Biostatistics, Abstracts, Dissertations and Theses, Reports, Research Papers, Presentations, Curriculum Development, Fact Checking
Technical — Statistical Analysis, Tutorials and Training Materials, White Papers, Reports
Social Science — Statistical Analysis, Market Research Survey Design
Business — Statistical Analysis
----SPSS, SAS, statistical analysis, developing methodology for experiments, statistics tutor (will provide lecture notes that explain statistical techniques simply), data entry, preparation of tables and graphs, writing reports of findings, nonparametric data analysis, time series analysis, spectral analysis, forecasting and prediction, spatial analysis, design of experiments, hypothesis testing, principal component analysis, Anova and regression analysis, clustering methods, applying statistical methods to scientific data (e.g. environmental science, biology, physics), applying statistical methods to social science data (e.g. psychology, sociology, economics), applying statistical methods to financial data (e.g. finance, business, and marketing), survey design, distribution fitting of data, statistics education of non-math majors.

Additional information

Dr. William Nasby received his Ph.D. in Personality and Development/Applied Multivariate Statistics from Harvard University in 1980 and his B.A. in Psychology from Brown University in 1975. His expertise in applied multivariate statistics spans numerous techniques, including (but not confined to) multivariate analysis of variance and covariance, the multivariate approach to analyzing repeated-measures designs, discriminant function analysis, multivariate multiple linear regression, canonical correlation analysis, principal components analysis, factor analysis, dynamic factor analysis, cluster analysis, multidimensional scaling, and time-series analysis.

With over 20 years of experience as a professor, first at a major university and then at a doctoral program in clinical psychology (APA-accredited), Dr. Nasby received numerous awards for excellence and innovation both in teaching and in research. His teaching awards include courses in Research Methodology, Introduction to Statistics, Intermediate Statistics, Multivariate Statistics, and Alternative Methodologies.

Additional information

Educational Psychology Advisor
Elizabeth L. Pearman, Ph.D. has spent more than 17 years designing surveys, analyzing data using SAS and SPSS, programming SAS and SPSS, developing assessments for unique situations, research design, developing sampling frames, calculating sample size, program evaluation, qualitative design, and qualitative analysis. Along with being an independent consultant in program evaluation, she teaches graduate classes Master's and Doctoral level research methods, qualitative methods, program evaluation, statistical programming, and lifespan development at the University of Northern Colorado for the Department of Applied Statistics and Research Methods and the Department of Educational Psychology.

Elizabeth has completed over 40 program evaluations for clients, made more than 40 presentations at national conferences, published articles in several different fields, and authored three books. She has served on 25 dissertation committees and has consulted with another 40+ doctoral students on design, statistics, statistical programming, conceptualization, and writing in fields diverse as: sports administration, special education, educational leadership, human rehabilitation, educational psychology, applied statistics, school psychology, music education, chemistry education, biology education, instructional technology, psychology, reading, early childhood, and others. Her formal education includes a B.M. from the University of Missouri at Kansas City, an M.A. and Ph.D. from the University of Northern Colorado in Educational Psychology specializing in research methods, measurement/assessment, program evaluation and statistics.

Betsy can help you with all phases of your dissertation/thesis from conceptualizing the dissertation/thesis, use of qualitative methods, qualitative design, qualitative analysis or quantitative methods. Her statistical skills are extensive (descriptive, inferential, multivariate, regression analysis, factor and cluster analysis, and reliability and validity, etc.) along with expertise in survey/questionnaire design and development, methodology chapter editing, sampling techniques and sample size calculation, proposal development, defense preparation, web-based surveys, data entry, data editing, statistical programming, measurement/ assessment, data interpretation and understanding, experimental and quasi-experimental design, Internal Review Board applications, informed consent forms.

She can make statistics understandable, will help you develop and edit your methodology chapter, assist you in understanding your data, help you with formulating your research questions, and guide you from the conceptualization of your dissertation/thesis to the defense so you will learn and understand your data, results, and study.

"I simply would not have completed my dissertation without Betsy's help, she made it data understandable, interesting, and I learned a lot!" Dr. Charlotte Nicodemous, San Diego State University. Scope: Educational Psychology - Program Evaluation, Research Methods, Statistics, Measurement

Articles:
Identifying the Population and Variables

Additional information

Dr. Brian S. received his Ph.D. in criminology in 1999 from Florida State University. He currently is an Associate Professor of Criminal Justice, teaching criminal justice statistics. In his career, Dr Brian has instructed nearly a dozen classes that focus on research methodology and statistics.  He has overseen the statistical analyses of hundreds of undergraduate papers and has served as chair to over a dozen masters theses.  

Dr. Brian S. has a broad background in the statistical analyses necessary to complete dissertations and theses.  He has published papers using some of the most advanced multivariate statistical analyses in the field, while still using basic chi-square tests, t-tests, correlation coefficients and other common bivariate analyses.  He has a strong understanding of corrective tests to assure normality, heteroskedasticity, autocorrelation and multicollinearity of data.  He also has substantial experience publishing papers using linear, logistic and two stage least squares regression.

He has worked closely with both American and International students and he has experience with the criminal justice systems of other countries, spending a number of summers teaching abroad and studying criminal justice systems around the world.  He is an experienced online instructor and he understands how to clearly and expediently mentor students in statistical analyses through use of e-mail and chat sessions. 

Additional information

Dr. Jane Scott received her Ph.D. in quantitative psychology with an emphasis on personality psychology from the University of California, Davis. After teaching statistics and research methods for several years at UC Davis and in Hawaii while providing statistics consulting on the side, she now provides full-time statistics consulting. She lives on the island of St. Croix in the Caribbean where she enjoys sun and surf in addition to statistics.

Jane can help you analyze your data and interpret the results using SAS, SPSS, or Minitab. She can help you understand, implement, and interpret statistical procedures such as t tests (single-sample t test, independent t test, dependent or paired t test), ANOVAs (one-way ANOVA, two-way ANOVA, repeated measures ANOVA, MANOVA, ANCOVA), nonparametric procedures (chi-square, Mann-Whitney U test, Kruskal-Wallis, Wilcoxon, Friedman, McNemar, Cochran, Fisher’s Exact Test) correlation, multiple regression, logistic regression, factor analysis, principal component analysis (PCA), mediation, moderation, and cox regression, among others. She can run the appropriate analyses for addressing your hypotheses, make APA-style tables or figures for presenting your results, and guide you in the appropriate presentation of your results.

Jane can also provide simple explanations or computations for such statistical concepts as variance, standard deviation, z-scores and the normal distribution, the central limit theorem, type-I and type-II errors (alpha and beta), power, effect size, R-squared or the coefficient of determination, and the Pearson Product Moment Correlation Coefficient, as well as concepts from psychometrics such as reliability and validity.

Jane received her bachelor’s degree in English from the University of California, Berkeley, so she spent her undergraduate years developing her writing and communication skills, which enable her to communicate mathematical concepts clearly. She loves to help students hone their methodology chapters, formulate clear hypotheses, and clearly articulate the appropriate analyses for testing each hypothesis. An animated teacher and public speaker, Jane can also help you develop effective Power Point presentations for classes or oral defenses.

Statistical Skills
Statistics: t tests (single-sample t test, independent t test, dependent or paired t test), ANOVAs (one-way ANOVA, two-way ANOVA, repeated measures ANOVA, MANOVA, ANCOVA), nonparametric procedures (chi-square, Mann-Whitney U test, Kruskal-Wallis, Wilcoxon, Friedman, McNemar, Cochran, Fisher’s Exact Test) correlation, multiple regression, logistic regression, factor analysis, principal component analysis (PCA), mediation, moderation, and cox regression, among others.

Statistical Software: SAS, SPSS, Minitab

Additional information

Advanced Engineering Mathematics

Elana Shippen, P.E., is a licensed professional engineer in mechanical engineering with 22 years of experience, including 14 years in the aerospace industry with the Boeing Company (commercial airplanes program). Elana completed the Technical Writing and Editing Certificate Program at the University of Washington in 2001. She is experienced with various style manuals.

In addition to her mechanical engineering degree, Elana also holds a minor in mathematics and assists engineering and business students with:

• Editing academic and professional mathematics papers and journals, including engineering mathematics masters and PhD thesis
• Tutoring required math courses for engineering students, such as calculus and differential equations
• Providing educational consulting services in engineering mathematics

DJ Simons, MA, is a recent graduate of the University of North Carolina’s developmental psychology program, where he had a formal concentration in quantitative methods.  He has served as a teacher’s assistant many times, including four times for Statistics for Psychologists and twice for Research Methods for Psychology.  He has also served as a data analyst for a private education research firm, and has privately tutored undergraduate and graduate students in statistics.

DJ has aided students and colleagues through all steps of the research process, from formulating a research question and hypothesis, through data analysis, to reporting the results in a scholarly fashion using APA style.  He is happy to help undergraduate and graduate students with their statistics classes, master’s theses or doctoral dissertations in the social sciences, explaining every step of the process clearly and concisely.  He will make sure that you understand your data, and that you can speak intelligently on its content, use and application.

He can advise on, among other things, research methodology, ANOVA, ANCOVA, t-tests, linear, multiple and logistic regression, chi-square, factor analysis, and hierarchical linear modeling/multilevel modeling (HLM).  Although his background is in quantitative psychology, he can help with statistics for other social sciences such as Sociology, Social Work and Education.  He is highly proficient with SPSS, both menu-based and syntax, and can also help with SAS, SPSS, CEFA, and R.

Additional information

E.L. Zurbriggen has provided statistical consulting for numerous master's and Ph.D. theses, has taught doctoral-level statistics courses for the past 7 years and has presented statistical workshops at national conferences. She received a Ph.D. in Personality Psychology from the University of Michigan, and subsequently completed an advanced post-doctoral fellowship in probability, statistics, methodology, and quantitative techniques at New York University. Her areas of advanced expertise include analysis of variance (including ANOVA, MANOVA, ANCOVA), multiple regression, logistic regression, exploratory and confirmatory factor analysis, and structural equation modeling (SEM, using software packages such as LISREL, AMOS, and EQS). Her goals when consulting are threefold: to communicate the basics of the techniques as clearly as possible, to encourage the use of statistics as one part of a larger argument, and to promote student/client empowerment through mastery of (rather than robotic application of) statistical techniques.

Feedback