Statistics: theory and applications (R/Python/SPSS)

From 37 £ /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

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.

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

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

Statistics

Methodology course

Computer programming

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Empirical project supervision in academia and industry

37 £ /h

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.

Robert

4.74

(27)

A highly experienced Franco-Belgian teacher (ook in het nederlands!) offers private lessons in mathematics (including finance), probability and statistics, as well as physics, chemistry, and biology for secondary and higher education levels. For physics, chemistry, and biology, the instruction is tailored to the secondary level, specifically up to the 5th year of secondary education in Belgium.

Whether you prefer lessons at your place, my place, or remotely, I am flexible to accommodate your needs. If necessary, I can travel to your home in Brussels, Walloon and Flemish Brabant, with a minimum duration of 2 hours per session. The lessons are designed to provide extensive practice with numerous exercises. Distance learning options are also available through platforms such as Skype, Facebook, etc. Please note that for students in France, only distance learning courses are provided.

In mathematics, I specialize in various topics and frequently provide lessons covering the entire secondary school curriculum, including math 6 and higher. These topics encompass factorization, equations of the 1st and 2nd degree (with in-depth study of parabolas), limits, derivatives, integrals, exponentials and logarithms, as well as trigonometry. Additionally, I am occasionally called upon to teach analytical geometry in space, including equations of lines and planes.

For statistics and probabilities, I provide instruction in descriptive and inferential statistics (univariate and bivariate), covering confidence intervals and hypothesis tests, applicable to secondary and higher education levels.

Feel free to reach out to me to discuss and arrange the lessons based on your specific needs and availability. My aim is to help you enhance your skills effectively and provide personalized instruction. By tailoring the lessons to your requirements, we can ensure rapid progress in your studies.

Matías

4.74

(27)

Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Leila

4.74

(27)

I provide high-level instruction in university mathematics and statistics for students in STEM, Economics, Engineering, and Data Science programs. This class is designed for students who require conceptual depth, mathematical rigor, and practical analytical skills, not surface-level tutoring.

I teach core university subjects including Calculus I–III, Linear Algebra, Differential Equations, Probability, and Statistics, with a strong emphasis on understanding how mathematical theory is applied in real academic and research contexts.

My approach goes beyond standard problem-solving. I help students:

develop mathematical reasoning and proof-based thinking

connect abstract theory to applied models and real data

understand how mathematics underpins research papers and empirical studies

interpret formulas, graphs, and statistical results critically

move confidently between theory, computation, and interpretation

In addition to coursework support, I assist students with:

statistical analysis of research data

understanding and reproducing methods used in academic papers

regression analysis, probability models, and data interpretation

preparing mathematical and statistical sections of research projects

With extensive experience teaching at both international universities and research-oriented environments, including work as a Math and Statistics tutor at the University of Wisconsin–Madison, I understand the expectations placed on university students and researchers. I help students bridge the gap between lectures and independent academic work.

Sessions are structured, intellectually demanding, and personalized. I work with motivated undergraduate and graduate students, as well as adult learners who need mathematics for research, professional growth, or advanced study.

Sincerely,

Leila

Madara

4.74

(27)

I am a Doctor of Psychology (PhD) and researcher with extensive experience in teaching and mentoring. Since October 2016, I have successfully tutored undergraduate, postgraduate, and Ph.D. students, as well as professionals, in areas including Psychology (AS, A-level (AQA or other exam boards), and degree level), Statistics, Data Analysis, SPSS, Jamovi, JASP, R/RStudio, Research Methods, and in support of research projects, theses, and dissertations.

I specialise in Clinical Psychology, particularly reading disabilities and dyslexia, though I also have strong knowledge across other areas of psychology, research methodology, and data analysis, with expertise in SPSS.

I offer individual, live, one-to-one online sessions via Zoom, tailored to your learning goals. I can also recommend relevant literature and provide resources from my own curated database to support your studies and research.

Amin

4.74

(27)

Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.

Hayat

4.74

(27)

This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.

Kevin

4.74

(27)

► EXPERT STATISTICS, DATA ANALYTICS, MACHINE LEARNING & AI TUTOR FROM SWITZERLAND
► UNIVERSITY, FOUNDATION, IB, A-LEVEL & INTERNATIONAL SCHOOL SUPPORT

I completed my Master’s degree in Business Information Systems at a Swiss University of Applied Sciences, where my academic background strongly combined mathematics, statistics, data analysis, analytical thinking and problem-solving. This technical and data-oriented foundation shaped the way I teach today: clearly, logically and with a strong focus on real understanding.

For many years, I have successfully supported students in Statistics, Data Analytics, Machine Learning and AI. My main focus is especially on Statistics — from basic descriptive statistics to advanced statistical methods, hypothesis testing, regression, probability distributions and interpretation of results.

I mainly use R for statistical analysis, data handling, visualisation and practical exercises. My goal is not only to help students calculate results, but to make sure they understand what the results mean and how to explain them correctly.

► STATISTICS, DATA ANALYTICS & AI SUPPORT

► STATISTICS & PROBABILITY
I help students understand descriptive statistics, probability, random variables, distributions, sampling, confidence intervals, hypothesis testing, p-values, correlation, regression and statistical interpretation. My lessons focus on explaining the logic behind each method, not just applying formulas.

► APPLIED STATISTICS WITH R
I support students in using R for statistical analysis, data cleaning, visualisation, hypothesis testing, regression models and interpretation of outputs. Students learn how to connect theory, calculation, code and real meaning step by step.

► QUANTITATIVE METHODS & RESEARCH STATISTICS
I help students with statistical methods used in business, economics, psychology, social sciences, science and university research. This includes choosing the correct test, understanding assumptions, interpreting results and presenting findings clearly.

► DATA ANALYTICS & DATA SCIENCE
I support students with data preparation, exploratory data analysis, visualisation, dashboards, summary statistics and practical interpretation. The focus is always on understanding the data and drawing meaningful conclusions.

► MACHINE LEARNING & AI FOUNDATIONS
For students working with modern data topics, I also provide support in the foundations of Machine Learning and AI, including regression, classification, clustering, model evaluation and practical applications. These topics are explained from a statistical point of view, so students understand the logic behind the models.

► UNIVERSITY, FOUNDATION & INTERNATIONAL COURSES
I support students in Statistics, Data Analytics, Business Analytics, Quantitative Methods, Econometrics, Research Methods and technical modules. I help with exam preparation, assignments, projects and practical data analysis tasks.

► HOW I TEACH

► I FOCUS ON REAL STATISTICAL UNDERSTANDING.
Statistics becomes much easier when students understand why a method is used, what the result means and how to interpret it correctly.

► I EXPLAIN FORMULAS STEP BY STEP.
Difficult formulas, tests and models are broken down into simple, logical parts so students can follow the reasoning clearly.

► I CONNECT THEORY WITH R PRACTICE.
Students learn not only the statistical theory, but also how to apply it in R, read the output and explain the result in proper academic language.

► I HELP STUDENTS CHOOSE THE RIGHT METHOD.
Many students struggle with deciding whether to use a t-test, chi-square test, ANOVA, regression or another method. I teach students how to recognise the correct approach from the question or dataset.

► I TRAIN INTERPRETATION AND EXAM TECHNIQUE.
Students learn how to structure statistical answers, write clear conclusions, explain p-values, interpret confidence intervals and present results professionally.

► I ADAPT EVERY LESSON TO THE STUDENT.
Some students need help with theory, others with R coding, assignments, research projects or exam preparation. I adjust every lesson to the student’s exact course, level and goals.

► YEARS OF EXPERIENCE WITH STATISTICS, DATA & UNIVERSITY STUDENTS

Over the years, I have successfully supported students from demanding academic programmes, helping them strengthen their statistical understanding, improve their analytical thinking and achieve excellent progress in Statistics, Data Analytics, Machine Learning and AI.

► ONLINE LESSONS

► Interactive whiteboard
► Clear digital notes
► Step-by-step statistical explanations
► R support for data analysis
► Exam preparation
► Assignment and project guidance
► Practical examples with real datasets
► Focused one-to-one support from Switzerland

► MY GOAL

My goal is not only to help students pass exams or complete assignments, but to help them truly understand Statistics. With the right guidance, statistical methods become logical, practical and much easier to apply.

► SUBJECTS: Statistics, Probability, Data Analytics, Data Science, Machine Learning, AI, Quantitative Methods, Research Methods, Econometrics
► MAIN TOOL: R
► LEVELS: International School, IB, A-Level, Foundation Courses, University Modules, Professional Training
► FORMAT: Online tutoring from Switzerland
► FOCUS: Statistical understanding, R practice, interpretation, exam preparation, assignments, projects and long-term analytical confidence.

Brent

4.74

(27)

Are you drowning in countless formulas? Is your head starting to explode with equations and graphs? Don't panic! Math doesn't have to be a stumbling block. With the right explanation and a calm approach, it often becomes much clearer. Together, we'll tackle it step by step, at your pace.

For whom?
- Students from primary and secondary education
- Children and young people preparing for exams or tests
- Anyone who wants to give mathematics a second chance, including adults

What can you expect?
- I explain the often complicated mathematical language in clear, human language
- Focus on insight, not just learning tricks and formulas by heart
- Exercises that we tackle together
- Space for questions, repetition and building self-confidence
I can also prepare exercises and even complete practice exams myself.

About me
I'm currently pursuing my Master's degree in Data Science/Analytics at the University of Antwerp. In high school, I had seven hours of math a week and always passed my exams with high marks. I've been happily tutoring students of various levels for several years now. I'm analytical, but also calm, patient, and good at sensing exactly where things are going wrong.

Practical:
- 1-on-1 lessons, online, at my place or at yours (if you don't live too far away)
- We will go through your material together or I will provide my own material
- Your own pace and approach, completely tailored to you

I have already successfully guided students with:
- Mathematics in secondary education: from the 1st to the 6th year, for various fields of study and schools, including Latin at Sint-Michielscollege Brasschaat, Economics-Mathematics at KA Schoten, and Humanities at Annuntia.
- Arithmetic in primary education: pupils in the 4th, 5th, and 6th grades, including mental arithmetic, written calculation, and other arithmetic skills.
- Mathematics in the Electromechanics program at AP University of Applied Sciences.

Feel free to send me a message with your questions or concerns, and we'll discuss how I can best support you.

Kevin

4.74

(27)

It is true that the philosopher is the friend of wisdom, but above all, he is someone who does not want to make mistakes in reasoning. Philosophizing is a way of reasoning and a way of solving problems that will never have a perfect and definitive solution. Knowing the distance between the Earth and the Moon is not a problem of philosophy, because it is enough to measure to solve it. On the other hand, knowing, for example, what justice is, is a problem of philosophy. A meter will not be able to help us know the answer. We must go about it differently, and in the courses I offer, I will teach you how.

You will learn

- text reading strategies
- case studies with the aim of learning from experts
- methodology in philosophy
- writing an essay
- writing a text commentary
- a work on the philosophers of your choice
- an overview of the history of philosophy
- the general culture necessary to be able to philosophize

I will adapt to your individual needs. Each course is tailor-made. We will analyze where your difficulties lie and together develop a course program that will make you perform as quickly as possible. The basic principle of the courses I offer is dialectics, like Plato's dialogues: reflecting together, making theoretical contributions, asking questions and seeking answers, and testing the validity of reasoning.

For the past 10 years, I have been teaching German using the philosophy methodology, having studied philosophy at the Master's level at Aix-Marseille University. It turns out that the analytical mind is very useful even outside the confines of philosophy. Today, there are even fields of activity such as management with philosophy or philotherapy. In recent years, some German students have asked me to also teach them philosophy courses, and that is why I decided to offer philosophy courses directly.

I look forward to meeting you during a first lesson.

Marc

4.74

(27)

🎓My name is Marc, I have a Master 2 degree in Applied Mathematics and Statistics and a Master 2 degree in Mathematics.
I teach mathematics and computer science to the following levels:
• Middle school (all grades)
• High school: common core curriculum, mathematics specialization, advanced mathematics
• Higher education: BTS, BUT, Bachelor's degree, private schools (probability, statistics, analysis, algebra, etc.)

📍 Areas of intervention
• At home: Marseille
• Online: throughout France (video conference lessons, shared materials, exercises sent after the lesson).

🧠 My method
• Review of the basics to fill in the gaps
• Simple explanations + concrete examples
• Targeted exercises to prepare for tests, exams, baccalaureate, midterms, etc.
• Implementation of a work method (worksheets, time management, writing)

🧮 For whom?
• Students who are struggling and want to improve their grades
• Students aiming for a good grade in the Brevet/Bac exams
• Higher education students who want to succeed in their math/statistics/computer science (python) exams.

⏰ Availability
• In the evenings on weekdays, and it's possible during the day on certain days of the week.
• Weekends
• School holidays (possibility of revision courses in small groups).

Farouk

4.74

(27)

These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework

Ali

4.74

(27)

I offer one-to-one Programming tuition in Python, C, and C++, for GCSE Computer Science, A-Level Computing, and university students studying engineering, computer science, or related subjects. Lessons are available online or in person around Birmingham.

What I cover:

Python for beginners and intermediate learners
C and C++ programming
GCSE and A-Level Computer Science (all exam boards)
University coursework support, debugging help, and project guidance
Core concepts: variables, loops, functions, data structures, object-oriented programming, file handling, basic algorithms

How I teach:
I start by understanding exactly where you are — whether that's "I've never coded before" or "I'm stuck on a specific assignment." Then I build lessons around small, practical examples you can actually run and modify yourself. I'm patient with errors (everyone gets them), and I make sure you understand the why behind the code, not just how to copy it. For university students, I can also help with debugging, code reviews, and explaining tricky concepts in plain English.
If you or your child is preparing for exams, working on coursework, or just wants to finally feel comfortable with coding, I'd love to help.

Baia

4.74

(27)

Many students lose confidence in math over the school year - not from lack of ability, but from pace, gaps, or one bad unit that never got resolved. This summer program (through mid-September) is built to fix that before the new year starts, not just review generally.
I work with middle and high school students, including IB, to close specific gaps not a broad refresher, but targeted work on exactly what's holding a student back. I bring the same structured, evidence-based approach I use with my university-admission students: identify precisely what's missing, build a plan around it, and track real progress, not just hours logged.
Best for students who want a calm, focused reset before the new academic year begins not for open-ended tutoring with no target

Fisnik

4.74

(27)

Do you have a statistics or probability exam in BA1/BA2? I can help you review the material in a clear, structured and exam-oriented way.

I support higher education students (university and college), particularly in their first and second years of undergraduate studies, to understand important concepts, redo practical exercises, and practice with exam-style questions.

My goal is simple: to help you understand the logic behind formulas, know when to use them, recognize correct reasoning in a statement, and gain autonomy when facing exercises.

Subjects covered according to your program:

• Descriptive statistics:
mean, median, variance, standard deviation, quartiles, quantiles, coefficient of variation, box plots, histograms, graphs, interpretation of tables and data.

• Univariate and bivariate statistics:
analysis of one variable, analysis of two variables, scatter plots, covariance, correlation, regression line, coefficient of determination, interpretation of relationships between variables.

• Probabilities:
events, union, intersection, complement, conditional probabilities, independence, Bayes' theorem, probability trees, contingency tables.

• Combinatorial probabilities:
permutations, arrangements, combinations, draws with or without replacement, counting, classic exam situations.

• Random variables:
discrete and continuous variables, probability function, density function, distribution function, expectation, variance, standard deviation, variable transformation.

• Probability laws:
Bernoulli distribution, binomial distribution, normal distribution, standard normal distribution, Student's t-distribution, chi-square distribution, use of statistical tables according to your course.

• Statistical inference:
sampling, estimators, point estimation, confidence intervals, margin of error, degrees of freedom, confidence level.

• Hypothesis testing:
null hypothesis H0, alternative hypothesis H1, significance threshold, p-value, one-tailed or two-tailed test, test on a mean, test on a proportion, chi-square test, interpretation of results.

• Exam preparation:
reading statements, choosing the right method, identifying the formulas to use, typical exercises, past exams, guided corrections and problem-solving methods.

Method of working :

1. We quickly identify the chapters that are causing problems;
2. I re-explain the theory with simple examples;
3. We redo the important exercises together;
4. I will show you how to recognize good reasoning in the exam;
5. We construct a clear method that can be reused independently.

I don't just provide a correction: I explain the reasoning step by step so that you are able to redo the exercises without help.

For students retaking the exam, I also offer more intensive support: level assessment, priority identification, review of fundamentals, and practice with typical exercises and past exams. The goal is to get straight to the point and work efficiently within the time available before the exam.

I have been giving private lessons for over 7 years in mathematics, statistics, economics, and accounting. I have also tutored first and second-year Bachelor's students at Solvay/ULB in mathematics, statistics, and microeconomics as part of a university tutoring program.

My professional experience in finance and business controlling at Deloitte has also allowed me to develop a very structured approach to numbers, analysis and problem-solving.

Courses available in French or English, online or in person in Brussels or the surrounding area.

Hajer

4.74

(27)

Struggling with Probability & Statistics at university? I help you go beyond memorizing formulas and learn how to THINK, SOLVE, and APPLY.

I am a university mathematics lecturer with several years of experience teaching university-level mathematics. My classes are designed especially for students in Computer Science, Engineering, Data Science, Mathematics, and other STEM programs.

We work on:

• Descriptive statistics: populations, variables, distributions, measures, tables and graphs
• Probability: events, conditional probability, independence, Bayes’ theorem
• Random variables and probability distributions
• Expectation, variance and standard deviation
• Discrete and continuous distributions
• Statistical inference and hypothesis testing
• Exam preparation and problem-solving strategies
• Understanding difficult exercises and choosing the right method

My approach is practical and student-centered. We do not simply review the lesson. We learn how to read an exercise, identify the important information, choose the appropriate concept or method, solve step by step, and avoid common mistakes.

Each session can include:
✓ A short diagnostic of your difficulties
✓ Clear explanations adapted to your level
✓ Guided problem solving
✓ University-level exercises
✓ Detailed corrections and feedback
✓ Exam-oriented practice

Whether you are struggling with the basics, preparing for an exam, or aiming for a higher grade, we will build a clear and effective strategy based on your actual needs.

Let’s turn Probability & Statistics from a difficult subject into a subject you can confidently solve.