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from48.29USD/ h

Empirical project supervision in academia and industry

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.

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 via webcam

General info

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

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.

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

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
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

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Availability of a typical week

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from $48.29Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

Online reputation

  • Instructor since October 2022
  • Phone number verified
  • Google connected
  • Linkedin connected

Availability of a typical week

(GMT -04:00) New York
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from $48.29Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

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Radouan
Comprehensive Thesis Support in Statistics, Probability, and Data Analysis Using R
Comprehensive Thesis Support in Statistics, Probability, and Data Analysis Using R For Bachelor’s, Master’s, and Doctoral Students – All Disciplines Are you currently preparing your final thesis, research paper, or academic dissertation and struggling with the statistical component, data analysis, or the use of R software? I offer specialized, high-level academic support for students and researchers needing assistance in designing, executing, and presenting quantitative research using rigorous statistical methods and advanced data analysis with R. --- Who I Help Students and early-career researchers in fields such as: Economics, Finance, Business & Marketing Management & Human Resources Psychology, Education, Sociology & Political Science Public Health, Epidemiology & Medicine Engineering, Environmental Sciences & Urban Studies Data Science, Computer Science, Mathematics & Machine Learning Whether you're a beginner in statistics or already comfortable with data but unsure how to structure your work academically — I adapt to your needs. --- Detailed Services Offered 1. Research Design & Statistical Methodology Refining research questions and translating them into statistical hypotheses Identifying appropriate study designs (experimental, quasi-experimental, cross-sectional, longitudinal, etc.) Selection of variables, metrics, and scales Determining sample size and statistical power (power analysis) Building conceptual and analytical frameworks 2. Data Analysis Using R Data cleaning and wrangling (dplyr, tidyr, data.table, etc.) Exploratory data analysis (EDA) with graphical and statistical summaries Statistical testing: t-tests, ANOVA, chi-square, Mann-Whitney, Wilcoxon, etc. Regression models: Linear regression Logistic regression Multinomial and ordinal regression Poisson and negative binomial models Panel data models Multivariate techniques: PCA (Principal Component Analysis) Factor Analysis Cluster Analysis (k-means, hierarchical) Correspondence Analysis Machine Learning (optional): Decision trees, Random Forests, SVM, etc. Time series analysis (ARIMA, Holt-Winters, Exponential smoothing) Data visualization using ggplot2, plotly, shiny dashboards (on request) Code optimization and creation of custom reusable scripts 3. Writing and Structuring Statistical Sections Assistance with writing the methodology and results sections: In proper academic English (or French) With clarity, scientific accuracy, and structured argumentation Proper interpretation of p-values, confidence intervals, effect sizes, R2, etc. Integration of graphs, tables, and summary statistics directly from R Help with organizing appendices (data tables, code snippets, raw outputs) 4. Proofreading, Review, and Feedback In-depth review of your full draft Correction of technical and logical inconsistencies in the statistical reasoning Advice on improving academic flow and clarity Formatting guidance (APA, MLA, Chicago, Harvard, etc.) 5. Coaching & Pedagogical Support One-on-one coaching sessions tailored to your level and project Explaining every concept and technique so that you understand and own your thesis Simulation and walkthrough of a potential thesis defense or presentation Tips on how to explain your statistical choices and justify your findings to your supervisor or jury --- Languages & Communication Work in English or French Clear, responsive communication Support available via email, Zoom, Google Meet, or your preferred platform Live screen sharing, real-time R coding, file exchange, and collaborative editing via Google Docs or Overleaf --- Flexible and Transparent Work Format One-time assistance (specific problem or section) Ongoing support throughout the thesis process (several weeks/months) Help available even on weekends and evenings Discretion, confidentiality, and academic integrity guaranteed --- Why Work With Me? Over 20 years of experience in mathematics and teaching Master’s degree in Mathematics with specialization in mathematics education and applied statistics Practical expertise as a data analyst, working on real-world datasets and academic projects Strong command of R, as well as experience with SPSS, Excel, Python (on request) Successful track record of supporting dozens of students in completing theses in Europe, North Africa, and North America