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)

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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."

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Tom Granoff, Ph.D. has spent over 25 years designing surveys, analyzing data using SPSS or SAS and writing the results chapter for hundreds of theses and dissertations in most of the behavioral sciences. Tom often edits the Methods Chapter to ensure the research questions hypotheses, data gathered and the statistical analysis approach are all in agreement. He worked on over 200 separate projects in the past 24 months.

Frequent majors Tom works with include 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 at 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 math. Clients also frequently ask Tom to help them prepare for their final orals.

His formal education includes a Ph.D. in Clinical Psychology plus Master's degrees in Theology and Industrial/Organizational Psychology.

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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.

"Using Ron was the best decision we made about our graduate research project. While we knew the field of anesthesia, none of us were statisticians and we struggled greatly in making sense of our data. Ron simplified everything and had most of our questions answered within 48 hours of our initial request. Excellent service and quality."

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Dr. Chad Martin received his doctoral degree in Healthcare Management from Tulane University, School of Public Health and Tropical Medicine. His master�s degree is in Exercise Physiology and Management. He is also a Registered Exercise Physiologist with the American College of Sports Medicine.

Dr. Martin has worked in healthcare for the last 15 years. As a biostatistician he conducts many types of analyses, such as performance improvement, market share, clinical quality, and staffing effectiveness. Further, he serves as the biostatistician for the Cardiac and Pulmonary Rehabilitation Association in NC.

He has taught online for several universities in their respective undergraduate and graduate degree programs in Healthcare Management. As a subject matter expert, he has helped universities with course design for healthcare finance, quality, and outcomes research/classes. He has served on doctoral dissertation committees and chaired three.

He also has a great deal of experience and interest in cardiac and pulmonary rehabilitation research. He has recently published several new studies in the cardiac and pulmonary area (July/August 2008 issue of the Journal of Cardiac and Pulmonary Rehabilitation). He is also interested in Medicare and Medicaid data mining, predictive modeling, and secondary data analysis.

During the data gathering phase:
* develop specific methods to reduce time
* create data set templates to enter data from research
* assist with validity and reliability
* select the most appropriate survey instrument or measurement tool

During the data analysis phase:
* select the most appropriate data analysis techniques
* statistical analysis and interpretation
* graphing and charting of data During the write-up phase:
* compile the data into usable and clear language
* select the most appropriate charts and graphs to include
* have conclusions that correspond throughout the paper

During the thesis or dissertation defense preparation phase:
* coaching regarding the statistical interpretation of data that will be presented.

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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 subject-matter expertise spans a wide range of psychological subfields, including Personality, Developmental Psychology, Social Psychology (especially social cognition), Evolutionary Psychology, the Psychology of Emotion, Cognitive Experimental Psychology (especially the interactions between affect and cognition), and Clinical Psychology (notably major depression, anxiety disorders, dissociative disorders, PTSD, and the evaluation of treatment outcome and therapeutic process). In addition, Dr. Nasby has attained professional recognition for his expertise in Multivariate Statistics, Psychological Assessment (clinical and personality), Psychometrics (psychological measurement as well as test construction and evaluation), and Research Design/Methodology.

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 Personality (Theory, Research, and Assessment), Psychological Assessment, Psychology as a Social Science, the Cognitive-Affective Bases of Behavior, Research Methodology, Introductory Statistics, Intermediate Statistics, Multivariate Statistics, and Alternative Methodologies.

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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. She has served on 25 dissertation committees and has consulted with another 40+ doctoral students on design, statistics, statistical programming, and conceptualization. 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.

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Dr. Jane Scott approaches statistics with the same motto that she uses in life: “Keep it simple and have fun with it!” Jane received her Ph.D. in Quantitative Psychology with an emphasis on personality psychology from the University of California. She teaches statistics for psychology at S. Pacific university, where they let her wear shorts and teach barefoot. Her students often leave her class amazed that they have come to like a subject of which they were 2initially frightened.

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, mixed ANOVA, MANOVA), correlation, chi-square, multivariate procedures (multiple regression, logistic regression, factor analysis, principal component analysis or PCA), and survival analysis, among others. She can also provide simple explanations 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.

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Dr. Jan Visser earned his Ph.D. in psychology in 1998. He worked as an assistant professor and currently combines teaching with a career as a fiction author. Jan has published twelve academic texts and two fiction novels. His scholarly writing is clear, concise, and to the point, while his creative writing can be described as passionate and engaging. Jan teaches Scholarly Writing and Research Design for Walden University, and he has extensive experience guiding students through the process of writing their thesis or dissertation. He consistently receives excellent evaluations from his students, who praise his commitment and the quality of his feedback.

Jan will help you design your research and write your thesis or dissertation. He can also give general advice on the use of statistics. His strengths include:

1. A thorough knowledge of research design and statistics, including t-tests, ANOVA, MANOVA, regression analysis, factor analysis, and cluster analysis—he can help you determine what type of analysis you should use for your particular research question.

2. A talent for spotting weaknesses in the design of a study—if you're still in the early stages of your research, he can help you improve your design and put you on the right track.

3. A knack for presenting complex material in easily accessible prose—he will not write your thesis or dissertation for you, but he will assist you in creating a well-written, comprehensible text.

4. Attention to detail—although Jan does not do copy-editing, he will point out errors in spelling and grammar, as part of his writing assistance.

5. A quick turnaround time—you'll have your stuff back before you can say floccinaucinihilipilification (this is a word, believe it or not).

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Dr. 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.

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