Statistics: theory and applications (R/ Python/ SPSS)
From 69.98 C$ /h
This class will provide students with private tutoring tailored to the needs of their BSc./MSc. classes, enriched with additional educational material and personalized explanations based on the scope and level of their course. The tutorials may cover statistical/econometric material for analyses pertaining to the disciplines of psychology, economics, policy evaluation, management, political science, sociology and more.
This class may cover any of the following topics:
- Hypothesis Testing, Analysis of Experimental Data, Power, Effect Size
- Parametric Inference and Estimation (i.e., regression, t-test, chi-square test)
- Causal Inference with Observational Data (i.e., instrumental variables, difference-in-differences, regression discontinuity)
- Probability Theory (i.e., LLN, CLT, probability distributions, Bayes theorem)
- Non - parametric and Machine Learning methods (i.e., supervised classification/regression techniques, unsupervised/clustering techniques)
- Coding in R, Python and SPSS
- Quantitative methodology and evaluation of analysis results
This class may cover any of the following topics:
- Hypothesis Testing, Analysis of Experimental Data, Power, Effect Size
- Parametric Inference and Estimation (i.e., regression, t-test, chi-square test)
- Causal Inference with Observational Data (i.e., instrumental variables, difference-in-differences, regression discontinuity)
- Probability Theory (i.e., LLN, CLT, probability distributions, Bayes theorem)
- Non - parametric and Machine Learning methods (i.e., supervised classification/regression techniques, unsupervised/clustering techniques)
- Coding in R, Python and SPSS
- Quantitative methodology and evaluation of analysis results
Extra information
Lessons can be held online (via Zoom, Skype or some other preffered platform) or at a physical location if possible. It is also possible to schedule classes with more than 1 person (max 4).
Location
Online from Netherlands
About Me
I have worked as a full time Lecturer and Tutor at Erasmus University Rotterdam for more than 6 years, teaching several courses in statistics and quantitative methods, as well as supervising students in their BSc. thesis. At the moment I work as a Data Scientist at a large consulting firm in Amsterdam.
I have experienced the joy and rewards of teaching when students achieve their academic goals and I continue my teaching activities at Erasmus University as a guest lecturer. However, teaching small scale interactive classes is what I have always enoyed the most and would like to focus on.
I have received thousand student evaluations over the years and according to them some of my most salient characteristics as a tutor are: patience, clarity of explanations and the ability to create a safe environment for questions and reflections on the material. In my classes, students are placed in the driver's seat and learn from their mistakes at a pace that is optimal for them and their needs.
I have experienced the joy and rewards of teaching when students achieve their academic goals and I continue my teaching activities at Erasmus University as a guest lecturer. However, teaching small scale interactive classes is what I have always enoyed the most and would like to focus on.
I have received thousand student evaluations over the years and according to them some of my most salient characteristics as a tutor are: patience, clarity of explanations and the ability to create a safe environment for questions and reflections on the material. In my classes, students are placed in the driver's seat and learn from their mistakes at a pace that is optimal for them and their needs.
Education
MSc. Behavioural Economics, Erasmus University Rotterdam - Thesis: 8.5/10
MSc. Policy Economics, Erasmus University Rotterdam - Thesis: 9/10
Certificate Statistics & Data Science, MITx
MSc. Policy Economics, Erasmus University Rotterdam - Thesis: 9/10
Certificate Statistics & Data Science, MITx
Experience / Qualifications
6+ year of teaching experience in statistics and quantitive research methods at Erasmus University Rotterdam, including teaching small scale interactive classes, lecturing, designing high quality interactive teaching material, thesis supervision and coordination of large classes with 200+ students.
Courses:
- Quantitative Research Methods & Analysis with R
- Intermediate Statistics I & II
- Introduction to Statistics & SPSS
Courses:
- Quantitative Research Methods & Analysis with R
- Intermediate Statistics I & II
- Introduction to Statistics & SPSS
Age
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
90 minutes
120 minutes
The class is taught in
English
Greek
Skills
Availability of a typical week
(GMT -05:00)
New York
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
This class will provide students with personalised, end-to-end guidance/supervision in empirical research projects. This could entail BSc./MSc. theses, academic projects/assignments or industry related work. These classes will provide hollistic support in all aspects of the empirical project, from data understanding, analysis, careful interpretation of the results and presentation through captivating and coherent storytelling. The class can also provide support with code implementation in R/Python/SPSS.
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