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1Students

The lecture includes - Explanation of all econometric topics from the basic to the advanced level. - Simplifying concepts and theories in a clear and easy-to-understand style. - Explanation of econometric models from basic to advanced, including simple and multiple linear regression, ECM, VECM, ARDL, VAR, and time series models, with interpretation of statistical results and their practical application. - Training on solving assignments and tests with a detailed explanation of the solution steps. - Assistance in using statistical analysis software such as EViews, Stata, and SPSS. - Explaining how to interpret the outputs of statistical programs and write the results in an academic manner. - Providing practical examples and applications to reinforce understanding. - Answering all student inquiries during the session. Suitable for Undergraduate students. Graduate students. Researchers who wish to apply econometrics in their research.

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Probability & Statistics can be challenging at times. If you're struggling to find the intuition and natural understanding of statistics, we will develop this together. With 7 years of experience in tutoring statistics, I can confidently claim you will leave the session able to explain the concepts to your friends & family, and even back to me. If you need exam prep or just need to develop an intuition of Stats and/or Probability, I got you!

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If you are studying in the Faculty of Economics or the Faculty of Commerce and Business Administration and you want someone to help you with the subjects that are difficult for you and you are unable to understand them on your own. If you are weak in one or more subjects, don't worry at all. I will start with you from scratch until you get the best grades. I will be your guide on your study journey and walk with you step by step. We will also do graduation projects together. Success is guaranteed, God willing

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15Students

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.

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14Students

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.

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1Students

Currently in Master 2 of Random Modeling at the University of Paris Cité, after a rigorous research Master focused on dynamic systems, I dedicate my expertise to Bachelor (L1, L2, L3) and Master (M1) students facing the demands of scientific and economic fields. Objective: Zero obstacles. A targeted support system to help you pass your exams and entrance exams.

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2Students

Demystifying probabilities and data processing Statistics and probability occupy an increasing place in the secondary school curriculum and directly prepare students for the requirements of higher education (economics, medicine, engineering, humanities). The sessions will include: Descriptive statistics (means, standard deviations, graphical representations). Conditional probabilities, probability laws and combinatorics. Analysis, interpretation of datasets and sampling logic. Targeted training based on typical exercises and exam problems.