Dr. Larissa B has a Ph.D. in Industrial-Organizational Psychology, with a minor in Research Methodology and a certificate in University Teaching Skills from Saint Louis University. She also has a Master?s of Science (Research) in Psychology and a B.A. in Psychology (minor in Criminology and Criminal Justice). As a graduate student, she received awards in teaching, research, and leadership/service. She particularly enjoys working with students who are new to research methods and statistics, focusing on easing statistical/math anxiety and building positive attitudes towards statistics.

Teaching Experience and Skills
Larissa has over five years of teaching experience in research methods/statistics. She currently works as a statistics counselor, working with undergraduate students in various statistics courses and those completing research projects, capstones, or thesis work. She also holds workshops on understanding statistical concepts and choosing appropriate statistical tests. Larissa has also worked with graduate students on their statistics coursework/ theses, including manuscript writing. Students who work with her find her to be patient, enthusiastic, warm, knowledgeable, accessible, and supportive.

Academic and Applied Research Experience and Skills
Larissa is a reviewer for multiple academic journals, and has considerable experience publishing in the following topic areas: psychology, education/educational psychology, business/management and organizational behavior, criminology and criminal justice. She currently has 12 peer-reviewed publications and 24 presentations in professional conferences. In addition to academic research, she has experience with working with non-profit organizations on projects related to organizational assessment/development and program evaluation. Larissa has a knack for producing ?client-friendly? reports for organizations that provide useful information without inundating the reader with statistical jargon and complex tables/graphs.

Areas of Expertise
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

"Although her publication record speaks for itself, Dr. B is quite exceptional with managing the research process. At the initial level, there are few who can cognitively synthesize research the way that she can. She is also very knowledgeable of data management and analysis. Perhaps more importantly, she is remarkably able to present and convey complex data in understandable forms—an invaluable skill for a teacher, researcher, or consultant. I have had the pleasure of working with her on multiple projects, and the outcomes have always been successful. She offers a great balance between presenting content and interpersonal skills. For example, despite being a subject-matter-expert, she communicates the material well and treats others with great respect. Furthermore, she genuinely has an intrinsic motivation for helping others, which is apparent with the enthusiasm and warmth she expresses towards others. It is with great privilege that I recommend her, as one of the most compassionate, hard-working, and intelligent individuals I have had the pleasure of knowing. She would be an invaluable asset to any student or institution." LaMarcus Bolton, Saint Louis University (graduate research work; contact information on request)

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Theresa Marie holds an M.S. in Statistics and a B.S. in Applied Mathematics from Texas A&M University. She worked several years at the statistical software corporation STATA where she provided data analysis support, taught online programming courses, and implemented statistical methodology to procedural commands. Her training with the software has enabled her to complete intensive data management projects, apply statistical analysis, and program statistical methodologies and mathematical computations.

As a statistical support representative, Theresa has assisted others with formulating a hypothesis, determining the correct statistical methodology to apply, fixing problems with data, interpreting statistical results, creating graphical interpretations of results, and constructing final conclusions. By answering over 7,000 support emails from STATA users, she has a wide range of statistical knowledge and can determine quickly the STATA commands needed to complete the analysis. As a software developer, she is also capable of programming detailed analysis and computations that may be specific to a project.

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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 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. 

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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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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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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, MATLAB, 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, 5. model creation and validation, 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

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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.

"Dr. Jane was terrific. She responded promptly to my queries, worked quickly and accurately. She was happy to provide options and spent as much time as necessary to see that I felt confident with the outcome." (Contact info on request)

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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.

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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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