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)

E-mail:
briones
at
helpwithstatistics.com

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John Bucci holds an M.S. in Statistics and a B.S. in Mathematics/Economics.

Mr. Bucci focused his Master’s studies in quantitative finance, specifically option pricing theory and econometrics.  He worked the past five years in the United States fixed income market as a portfolio manager and research analyst, during which time he applied the principles of mathematics and statistics to potential investment opportunities, the pricing of bonds with embedded options and macroeconomics such as monetary policy.

Mr. Bucci currently is a part-time lecturer in mathematics and introductory statistics, and he hopes to continue to share his experiences and qualifications both in the classroom and in his consulting services.  In general, Mr. Bucci can assist clients in all phases of their dissertation and/or data analysis projects, particularly in the understanding of basic probability and statistics concepts including:

• measures of central tendency and variation;
• counting rules and probability distributions;
• the Central Limit Theorem;
• confidence intervals, simple hypothesis testing and ANOVA;
• correlation and regression analysis.

For those clients specializing in mathematical finance, he can further assist in:

• Econometrics
• Times Series Analysis
• Modern Portfolio Theory
• Black-Scholes-Merton Option Pricing Theory (stocks and bonds)
• Interest Rate Modeling

Mr. Bucci enjoys working with all types of datasets and the various forms they come in.  He is highly proficient with scripting and data analysis in R and Microsoft Excel, and he also has experience working with: STATA, SAS, Matlab and Minitab.

bucci
at
helpwithstatistics.com

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Will Buchanan is currently a PhD candidate at TUI University where his dissertation research focuses on the causal effects of poverty on musical achievement in the US. He makes use of geospatial analysis (i.e., using ArcGIS software to measure resource allocation, concentration, and geographical differences in resource availability), econometrics (i.e., instrumental variable methods, regression discontinuity designs, differences-in-differences estimators, fixed-effects models, and others), and structural equation models (i.e., path analysis of observed data, latent variable modeling, etc…) to conduct quasi-experimental data analysis with a national data set from the US Department of Education. His use of multi-disciplinary approaches to research allowed him to integrate theory and statistical methodology from economics, education, and psychology. He has also provided statistical consulting and research services to a wide variety of public school districts, businesses, and institutions of higher education.

Buchanan is also an aspiring Stata programmer and has helped his clients automate their data analysis by providing custom-written Stata programs (i.e., .do and .ado). He also uses SPSS 16, LISREL 8.8, HLM 6.0, R, G*Power 3.2, ArcGIS, and other software packages to perform data analysis. Additionally, he uses StatTransfer 10 and is able to accept data files in almost any format and can provide data files in the format of your choice.

Specialties: music education, developmental psychology, neuropsychology, cognitive psychology, education, education policy, program evaluation, arts integration in education, econometric methods in educational research, contextual factors in education/developmental psychology, LaTeX typesetting software.

Articles:

Using Stata to Automate Summary Statistics in Longitudinal Data

What's New in STATA 12?

E-mail:
buchanan
at
helpwithstatistics.com

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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 SPSS, JMP, and R statistical software and programming languages.

E-mail:
lcampbell
at
helpwithstatistics.com

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Prof. Collins is Emeritus Professor of Psychology at UCLA. His numerous publications cover social psychology, applied social psychology, research methods, attitude change, persuasion, and social influence, Dissonance Theory, the design and evaluation of questionnaire measures, interviewing, health education, and community-based participatory research. These publications use a wide variety of statistical analyses. He served as Director of Research at Healthy African American Families II. He has taught at Yale and Stanford and was a Prof. of Sociology at the University of Wisconsin. He has written a textbooks on social psychology and research methods. He coauthored a book on Theories of Attitude Change. He has served and chair and vice chair of the human subjects protection committee (IRB). He has been an advisor for over a hundred undergraduate honors theses and MA and PhD theses. He has served as a social-psychology expert witness in court cases. His BS and MA were in communication at Northwestern University. He has focuses on one-on-one mentoring on activities ranging from: (a) the choice of a research topic that is relevant to the interests and skills of a particular student, (b) the identification of the most relevant theories, (c) the development of hypotheses, (d) research design, (e) the organization of research writing, (f) methods sections, (g) data analyses and the presentation results, and (h) the interpretation of results.

E-mail:
bcollins
at
helpwithstatistics.com

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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."

Note: All analyses performed with JMP.

E-mail:
efreeman
at
helpwithstatistics.com

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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.

E-mail:
tomgranoff
at
helpwithstatistics.com

Additional Information

Dr. Sarah H.

STATISTICAL GENETICIST
Quantitative Genetics
Genetic Epidemiology
Genotypic and Haplotype Tests
Hardy-Weinberg equilibrium
Genome-Wide Association Studies
Golden Helix
R Statistics – R Programming

Dr. Sara H. specializes in the analysis of genetic, biological, experimental, and clinical data. She is accomplished in the areas of statistical genetics, quantitative genetics, bioinformatics and biostatistics. Dr. Sara H. was trained in mathematics and biology (BA), statistics (MA), and genetics (Ph.D.). She worked as a statistical geneticist for The Rockefeller University in the Laboratory of Statistical Genetics, with Allan Award winner Dr. Jurg Ott. She works with researchers and clinicians from Baylor College of Medicine, Rockefeller University, and Casey Eye Institute.

For medical researchers and clinicians …
She crafts statistical analyses targeted to specific hypotheses and determines which statistics would best be applied to the biological questions. Working with a variety of scientists, she has contributed to the publication of over 35 peer-reviewed publications and research abstracts within the last five years. She has publications within the areas of heart disease, age-related macular degeneration, and drug addiction.

For graduate students in biology, genetics, bioinformatics, and biostatistics …
Sara teaches basic statistics courses as well as statistics courses specific to human genetics, and was formally trained as a statistical geneticist. As a statistical geneticist in a department of primarily molecular biologists, she developed an ability to communicate complex mathematical concepts clearly to both students and fellow scientists. With her combined training in both genetic epidemiology and statistical genetics, she has expertise in analyzing genetic data. Her Ph.D. thesis explored the role of context dependency and interaction in human genetics.

Summary …
She helps select and/or perform the proper statistical analyses for genetic, biological, and clinical data. She helps develop meaningful hypotheses with statistical analyses that reflect the biological questions being asked. She recognizes issues specific to biological and genetic data and understands how they may influence statistical analyses. As a medical communications consultant, she helps communicate research results in publications, presentations, and posters. Her purpose is not just to produce results, but to relate them understandably. She assists in the design of research studies or--if the research design is complete--performs the data analyses. She will work with you throughout the process to ensure that your questions are answered. She will either assist you in doing your own analyses or perform the analyses for you with a written report of the results. She has experience in writing grants, papers and presentations, both as a supporting statistician and as a first author. She also has experience teaching statistics and statistical genetics, and is available to provide consultation and statistical support to trainees on research projects. She can assist you in documenting the statistical methods used in the data analysis, in producing clean and comprehensible graphs and tables, in preparing bibliographic entries relevant to the statistical analysis, and in manuscript content drafting and review.
Sara H. also has expertise in both observational data (cross-sectional and longitudinal studies of patients and population studies of individuals) and experimental data (rats, mice, cell lines). Sara can help with issues such as linkage disequilibrium, inter-relatedness, and context-dependent effects.

Areas of advanced expertise: programming in R, genetic analysis of related individuals (e.g., generalized estimating equations, family-based association tests), genetic analysis of unrelated individuals (e.g., t-tests, analysis of variance, chi-square tests, logistic regression, genotypic and haplotype tests, Genome-wide association studies (GWAS), next generation sequencing analysis, interaction analyses (GXG, GXE, EXE)), and fitting data to the underlying assumptions (e.g., linkage disequilibrium, Hardy-Weinberg equilibrium, tests of normality, transformation of data), as well as traditional statistical analyses including, but not limited to, ANOVA, longitudinal analysis, survival analysis, linear regression, meta-analysis, power analysis, permutation testing, and various methods of correction for multiple testing.

All analyses are performed in R or using statistical genetics software such as Golden Helix. This allows her to deal with the large amounts of data being produced in the area of genetics, such as the million marker chips.

SaraH
at
helpwithstatistics.com

Additional information

Dr. Vicki Lawrence is an academic researcher who studies the epidemiologic nature of social conditions in relation to cardiovascular and other disease outcomes. More specifically, her work focuses on studies of poor health among African Americans and health disparities that may occur my age, race, and gender in cardiovascular and mental health outcomes. Utilizing her background in epidemiology and biostatistics, she has provided statistical support on multiple studies with various investigators commonly focused on physical and mental health data. In addition, she has worked with clinicians, research investigators, and tutored multiple graduate students as well in public health, epidemiology, social work, medicine, education, and nursing to tackle statistics related issues.

Dr. Lawrence takes a significant amount of effort to ensure the students and researchers she collaborates with or supports understand the theoretical rationale behind the methods appropriate for their research problems, meeting the students and researchers at their stage of understanding. In addition to explaining the foundations, she regularly provides each individual has the opportunity to ask questions, and explains the differences in statistical approaches as needed. Further, she can help develop data analysis plans, refine research questions, and examine data collection methodologies with clients as well.

In her own work, Dr. Lawrence has used exploratory/ descriptive analysis tools (such as t-tests) and nonparametric tests, ANOVA (including one way, two way, repeated measures and others), structural equation modeling, exploratory factor analyses, multilevel models, linear regression, logistic regression, multinomial regression, and growth curve modeling as well. She has prepared analytical methods sections for publications, including tables of regression outputs. Further, she can provide information relevant to epidemiologic methods, including prevalence, incidence, risk and rate ratios, causal diagrams (including mediating and moderating variables) and other topics as needed. She has used a variety of data sets of both large and small magnitude, including nationally representative public data sets such as NHANES and the Panel Study of Income Dynamics, but has also used survey as well as medical systems based data. She has substantial experience using SAS and Excel, and also uses HLM and SPSS.

"When I met Vicki, she was a breath of fresh air and hope as I knew she was the right person to teach me and get me through my statistics class. She was very knowledgable and was able to design her approach to my needs by presenting the material in a way I understood. I also contacted her to help my in my research class and again, she was very knowledgable, professional, and provided the instruction I needed. I would and will contact her again in the future as I continue my way through school. I highly recommend her to anyone needing assistance in statstics and research. Thank you Vicki for everything!!!" ~Jane DeLancey

"Vicki Lawrence did an extremely wonderful job with helping me understand the processes of statistics analysis. She was very patient and kind during the teaching process and made learning statistic fun." ~ Thanh Andrews

Compiling and Managing NHANES Datasets

Data Collection Methodologies for Health Research Projects

Vicki
at
helpwithstatistics.com

Additional information

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.

E-mail:
ronmarks
at
helpwithstatistics.com

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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.

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.

E-mail:
pearman
at
helpwithstatistics.com

Additional information

M Perrin received her MPH in Epidemiology from Columbia University and is currently a doctoral candidate in neuropsychology. Ms. Perrin worked as a Lead Scientist for the NYC Department of Health and Mental Hygiene. She helped develop a large-scale public health study and created surveys for assessing the psychological and physical health of survivors of the World Trade Center disaster. Ms. Perrin also provides mentorship to graduate-level statistics interns and teaches seminars in research methods and statistics to public health professionals.

Ms. Perrin received an award from the NYC Department of Health and Mental Hygiene for the year’s most impactful journal article and was invited to present her research at community and professional meetings. She has published 12 scholarly articles and presented findings at 13 scientific conferences. Ms. Perrin has also served as an ad hoc peer reviewer for 7 high-tier scientific journals, providing critical analysis of over 20 research studies.

Ms. Perrin is a statistical consultant for principal investigators and graduate students in psychology, education, pediatric endocrinology, psychopharmacology and neuroscience. She helps clients formulate testable hypotheses, devise accurate methods of assessment and conduct appropriate statistical analyses. She also provides critical review of written statistical reports to ensure that findings are presented in a clear and organized manner.

Ms. Perrin programs in SPSS\SAS and is familiar with AMOS, Matlab and STATA. Her statistical expertise include:

1. - Sample size and power calculations
2. - Reliability analysis (ICC, Chronbach’s Alpha)
3. - Pearson\Spearman Correlation analysis, T-tests
4. - Non-parametric analyses (Chi-square, Mann Whitney, Fisher’s Exact, etc.)
5. - ANOVA, ANCOVA, RM ANOVA
6. - Logistic and linear regression (univariate and multivariate)
7. - Survival analysis (Kaplan Meier, Cox Proportional Hazard Analysis)
8. - Structural Equation Modeling\Path Analysis
9. - Exploratory and Confirmatory Factor Analysis (Principal Component, Principal Factor Analysis)
10. - Hierarchical Linear Modeling\Mixed Model Regression Analysis\Canonical Correlation Analysis

Her research interests include:

1. - neurophysiology (ERP\EEG assessments)
2. - neuropsychology (auditory and visual processing, attention, memory and executive functioning)
3. - schizophrenia
4. - anxiety disorders\posttraumatic stress disorder
5. - psychiatric epidemiology\public health\behavioral health
6. - disaster\trauma

   "You were such a pleasure to work with. You removed the anxiety by explaining things in a simplified way that I could understand! I felt confident going into my defense and was able to cogently answer questions from my committee members. I would recommend you without reservation." Virginia De Sanctis

   "I cannot thank you enough for being such a patient and knowledgeable colleague. Without your expertise and guidance in data preparation and statistical analysis, our publications would never have been so well accepted by top-tiered journals. I truly appreciate and value your skills, patience, vision, and collaborative nature!" ~ Laura DiGrande, Dr.P.H., M.P.H.

    

Articles:

Growth trajectory during early life and risk of adult schizophrenia

Elevated maternal Interleukin-8 levels and risk of schizophrenia in adult offspring

Posttraumatic stress symptoms, PTSD, and risk factors among lower Manhattan residents 2–3 Years after the September 11, 2001 terrorist attacks

Differences in PTSD prevalence and associated risk factors among World Trade Center disaster rescue and recovery workers

Perrin
at
helpwithstatistics.com

Additional information

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.

E-mail:
dj
at
helpwithstatistics.com

Additional information