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Dear researchers, dear analysts, As you are well aware, statistics is a powerful tool. When used appropriately, it allows us to characterize complex systems such as human populations or neural networks. I hold a Ph.D. in physics from the University of Geneva. And previously, during my master's thesis, I conducted ab-initio calculations within a computational physics research group at EPFL (Swiss Federal Institute of Technology). Just like you, I understand the time investment required for properly understanding and utilizing certain tools. For those of you who recognize the importance of comprehending statistical techniques to conduct rigorous studies, you are right to seek guidance. So I am here to save you the time you need to focus on your work. Please feel free to contact me without hesitation. Sincerely,

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Msc Statitsics Biostatisticien CHUV-MERCK SERONO COurse until given for Pyschologists SSP, medical health, HEC and Geology. Using function import dataset format dataset cours pour UNIL UNINE UNIGE: Cours donné de la HEC au Psychologues...SSP Basic assumptions Probability and Laws (Distribution) COURS UNIL ou Lausanne gare aussi From regression-Anova to Chi squared.LMM Survival modelling Make with your statistics easy and verify your work and coding for Labo-Stat-practical session

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Graduated with a Bachelor's degree in Economics and Management from the University of Grenoble Alpes and a future Master's student in Management - Business Analytics orientation at HEC Lausanne, I offer targeted and individualized support in three areas: Statistics (Bachelor's / Licence level) • Helps to understand fundamental concepts (probabilities, inference, regressions, statistical tests). • Practical exercises to master the quantitative methods used in economics, management and social sciences. • Preparation for exams and setting up revision sheets. History-Geography (secondary / maturity / high school level) • Consolidation of knowledge and preparation for written and oral tests. • Methodology of document analysis, mapping and writing of structured compositions. • Deepening of major historical and geopolitical themes. Dissertation Methodology (all disciplines) • Learning techniques for constructing a clear and reasoned plan. • Work on the introduction, the problem, the transitions and the conclusion. • Practical advice to improve writing, logic and critical thinking. Method of working : • Individualized teaching adapted to the needs of the student. • Targeted exercises and homework after each lesson. • Regular reports to monitor progress. Objective: to help students progress effectively, gain confidence and develop solid methods for succeeding in their exams and university work.

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I am a student in a Master of Financial Engineering at EPFL and have a Bachelor in Mechanical Engineering as well as a Master from Ecole Centrale Paris. I did my primary and secondary studies at the Lycée Français in Brussels and then in Tunis, and obtained my bac with honors in the scientific section (Mathematics specialty). For information, I am tutor in Mathematics for first year EPFL (MAN 1A) and in Probability and Statistics for second year EPFL. I also helped several students in their preparation for the scientific baccalaureate / maturity (Math / Physics). I was thus able to develop a pedagogy adapted to the needs of each.

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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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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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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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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.