About Me

Statistical and Methodological Training and Experience

Graduate Coursework

Advanced Research Methods	Advanced Time Series Analysis	Bayesian Statistics	Categorical Data Analysis (logistic/probit, poisson/negative binomial models)
Geographic Information Systems	Linear Regression	Longitudinal/panel Analysis (x2)
Network Analysis	Probability	Research and Survey Design

Online Coursework

Websites: DC = DataCamp, STAN = Stanford Online Course
R
ARIMA Modeling^DC	Cleaning Data^DC	Cluster Analysis^DC
Data Manipulation with DPLYR^DC	ggplot2: Part 1^DC	ggplot2: Part 2^DC
Forecasting^DC	Importing Data: Part 1^DC	Importing Data: Part 2^DC
Importing & Cleaning Data: Case Studies^DC	Intermediate R^DC	Intermediate R: Practice^DC
Introduction to R^DC	Introduction to Time Series^DC	Manipulating Time Series with xts and zoo^DC
Marketing Analytics^DC	Multiple and Logistic Regression^DC	Supervised Learning: Classification^DC
Writing Functions^DC
Python
Cleaning Data^DC	Customer Analytics & A/B Testing^DC	Extreme Gradient Boosting with XGBoost^DC
Importing Data Part 1^DC	Importing Data Part 2^DC	Intermediate Python for Data Science^DC
Intro to Databases with Python^DC	Intro to Data Visualization^DC	Intro to Python for Data Science^DC
Linear Classifiers^DC	Machine Learning with Tree-based Models^DC	Manipulating DataFrames with pandas^DC
Merging DataFrames with pandas^DC	pandas Foundations^DC	Preprocessing for Machine Learning^DC
Python Data Science Toolbox 1 (Functions)^DC	Python Data Science Toolbox 2 (Iterators and List Comprehensions)^DC	Supervised Learning with scikit-learn (Iterators and List Comprehensions)^DC
SQL
Constraints and Triggers^STAN	Indexes and Transactions^STAN	On-Line Analytical Processing^STAN
Recursion in SQL^STAN	SQL^STAN	Views and Authorization^STAN

Teaching

I taught 2 semesters of an undergraduate research methods and statistics class, which covered survey design and sampling procedures, measures of central tendency and dispersion, standardization (e.g. z-scores), tabular and graphical displays of data using Microsoft Excel, statistical inference (e.g. confidence intervals and p-values), and a cursory introduction to linear regression. My syllabus can be found here.

About This Website

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