FINNERAN K. MUZZEY, MA
Statistics Training & Consultation
Statistics is story-telling. As a statistician, I am really nothing more than a story-teller. When I'm teaching statistics, I find that students and other folks I work with are often overwhelmed by a fear of math or a lack of confidence in computing math equations. I tell them, "I don't do math, I tell stories. And, as much as I'm going to teach some math, I'm more focused on teaching you how to tell a story with numbers."
It's true, statistics uses math, but (particularly social science) statistics isn't about the math as much as it's about the interpretation - the story. I take a practical approach to teaching statistics; What it is that you need/want to know? How can we get there? What tool is appropriate to answer this question? How do we honor our participants' truths through our interaction with this data?
It's true, statistics uses math, but (particularly social science) statistics isn't about the math as much as it's about the interpretation - the story. I take a practical approach to teaching statistics; What it is that you need/want to know? How can we get there? What tool is appropriate to answer this question? How do we honor our participants' truths through our interaction with this data?
My preferred stat programs:
SPSS - especially for data cleaning, data manipulation, and basic data analysis
Stata - especially for complex or advanced statistical techniques
I have a working knowledge of R and SAS, but they aren't my preferred programs of use.
I'm trained in the following areas, with both cross-sectional and longitudinal data:
I'm constantly adding more statistical tools to my tool bag, so inquire about something not listed!
SPSS - especially for data cleaning, data manipulation, and basic data analysis
Stata - especially for complex or advanced statistical techniques
I have a working knowledge of R and SAS, but they aren't my preferred programs of use.
I'm trained in the following areas, with both cross-sectional and longitudinal data:
- Basic descriptive data information
- Hypotheses testing; including t-tests, Chi-Square, ANOVA, etc.
- Mulitvariate and Univariate tests
- Regression analysis (linear, logistic, Poisson, ordinal, etc.); including mixed methods and generalized estimating equation techniques for longitudinal data
- Non-parametric testing; including exact tests, bootstrapping methods, etc.
- Multiple imputation and other missing data management techniques
- Factor analysis for measurement development
- Advanced and specialized techniques; including structural equation modeling, generalized structural equation modeling, propensity-score matching, latent class analysis, and linear growth curve analysis
I'm constantly adding more statistical tools to my tool bag, so inquire about something not listed!
I love teaching statistics and consulting with folks who have data but aren't sure what to do with it. If you'd like to work with me on a fun adventure through the land of statistics, please contact me through the contact page.