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I earned a B.A. Degree, with honors, at the University of Pennsylvania in Environmental Studies with a Geology minor. At Penn, I participated in internships and taught two semesters. For the internships, I worked with a field crew collecting soil samples on an environmental study with a Penn professor and doctoral student. The second internship was completed at the Smithsonian Environmental Research Center under a grant for undergraduate research (a REU grant) from the National Science Foundation. My work with the Smithsonian included managing the delivery of experimental treatments and collection of vegetation growth response data in an intertidal marsh ecosystem. The course I taught at Penn was Geology Laboratory, for which I won the Outstanding Teaching Assistant Award in 2009 from Penn's Department of Earth and Environmental Science.
In graduate school, I continued work on environmental research but focused on developing the statistical skills needed to manage data, develop studies, and form and test hypotheses. In addition I gained more experience teaching students. For graduate school, I attended the University of Idaho where I participated in an environmental research assistantship, a teaching assistantship, worked for the university's Department of Statistical Science as a statistics tutor, and earned a M.S. Degree in Statistical Science. I taught the College of Natural Resources's course Introduction to Geospatial Analysis. My research, training, and efforts in Idaho resulted in two professional scientific publications with scientists and funding from the U.S. Geological Survey and the U.S. Forestry Service.
Professionally, I have managed large datasets and written computer programs for data analysis, modeling, and simulation work. I have competency with the R Language and SAS software, and have familiarity with a number of statistical computing software packages. I completed 9 college level mathematics courses and 9 statistics courses at the graduate level. I wrote a statistics thesis on parameter estimability using novel and computationally intensive methods and got an 'A.' I have always enjoyed teaching and tutoring, and also have experience working with middle school students. I helped my nephew get selected for admissions to a competitive middle school in New York City for mathematics.
Biostatistics is the application of statistical theory to biological problems. Application of statistics to biology is arguably the oldest application of the most common statistical tools in use today, dating back to developments by R.A. Fisher and his peers.
My credentials to tutor and consult in biostatistics are supported by coursework, laboratory experience, internships, professional publications in which statistics are applied to biological processes, training and application of statistical computing software to statistical problems, and tutoring students in statistics.
My coursework has included completion of an M.S. Degree in Statistical Science at the University of Idaho (UI). Also at UI, I studied forestry and tree nutrition extensively, and I took a few courses in storing and analyzing spatial information in Geographic Information Systems (GISs). My undergraduate coursework was completed at the University of Pennsylvania (UPenn) which included courses in biology, chemistry, and ecology.
My scientific, research internships were biology related. I worked applying factorial designs with interactions, covariates, and fixed and random effects in mixed models to biological growth data. More generally, my research experiences apply regression to biological growth data suspected of being influenced under specific factors.
I have 3+ years of experience with the SAS software, 4+ years experience with the R language, and 6+ years experience with Microsoft Excel. In addition, during tutoring, I helped students learning to employ other software packages like Minitab.
Although the follow list is not exhaustive, I am competent to assist students in biostatistics courses in the following:
Types of Data
Steps in a Research Project
Numerical Summaries/Data Description
Visual Data Summaries
The Normal Distribution
Central Limit Theorem
t-Tests, including before-after pairing, match case control pairing, and independent samples tests
Risk and Odds Ratios
Types of Studies
Terrific and Flexible — Kevin was incredibly helpful to my son in a pinch. He helped him with AP Calculus and Statistics. We will definitely contact him again! ...
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