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(5 reviews)
Ahmed - Brussels, Belgium£57
£57Statistics Courses By a University Professor
Trusted teacher: In order to support students who encounter difficulties in statistics, remedial sessions on descriptive statistics and inferential statistics are offered in particular on: confidence interval, statistical hypothesis test, Paired data or not? "Normal" or not? Parametric and non-parametric tests, Confidence interval and "number of subjects needed" in estimating a proportion, Also the analysis of your thesis data (linear / logistic regression, anova, t-tests, principal component analysis, repeated measures, mixed models, time series, panel analyzes, fixed and random effects models, survival analysis, SEM, ...). Do you need to be accompanied to motivate you? I offer lessons to see or review together a chapter, a theme or others ... During these remediation sessions, I offer you various activities (Q&A sessions, resolution of standard exams, revision of concepts more difficult to integrate, etc.) which help students to fill in the gaps identified in previous courses. Passionate about mathematics and quantum physics, juggles with statistics on a daily basis in my BIGDATA research work, demystifies this test by the precise approach of the subjects via an adapted teaching whose key words - study methodology, - reasoning, and especially learning to reason differently - analysis and response strategies, - targeting of the problem - implementation of the link between theory and practice
Statistics
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Amine - Paris, France£36
£36Expert and experienced Professor: SPSS, R, jamovi, jasp, STATA, hypothesis testing, ANOVA, multivariate analysis, linear/log regression
Trusted teacher: During this course you will learn: ✓ SPSS ✓ R Studio ✓jamovi/jasp/Stata/xlstat ✓ Analyze data for univariate, bivariate and multivariate statistics with SPSS ✓ Simple and multiple linear regression and Logistic regression ✓ Analyze exploratory data, basic statistics and visual displays (Frequencies, exploration function, outliers) ✓ Inferential tests on correlations, counts and means (Calculation of z-Scores in SPSS, Correlation coefficients, A measure of reliability: Cohen's Kappa, Binomial tests, Goodness of fit test, Chi-square , One-sample t-test for a mean, Two-sample t-test for means) ✓ Analysis of variance (fixed and random effects, Running ANOVA in SPSS, The F-test for ANOVA, Effect size, Contrasts and post-hoc tests, Alternative post-hoc tests and comparisons, ANOVA with random effects , factorial ANOVA with fixed effects and interactions, Simple main effects, Analysis of covariance (ANCOVA), Power for analysis of variance) and Repeated Measures ANOVA (One-way repeated measures, Repeated measures in both directions: one between and one in the postman) ✓ Principal Component Analysis (PCA Example, Pearson 1901 Data, Component Scores, Principal Component Visualization, Correlation Matrix PCA) and Exploratory Factor Analysis (The Common Factor Analysis Model, The Problem of Factor Analysis exploratory, Factor analysis of CPA data, Scree Plot, Rotation of the factor solution, Cluster analysis, How to validate clusters) ___________________________________ ✓ My courses are based on exercises with the essentials of the course to remember. ✓ Working method for better understanding. ✓ Working on concrete data which allows the work to be visualized and assimilated more quickly.
Statistics · Math · Economics for students
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Abdou - Riyadh, Saudi Arabia£28
£28Statistics, Data Visualization, and Machine Learning for Beginners
📊 Introduction to Data Science with Python Full Title: Statistics, Data Visualization, and Machine Learning for Beginners (100% online course – for students, professionals in retraining, or curious data enthusiasts) Data science is now at the heart of the most innovative professions and strategic decisions in all sectors. However, when you're just starting out, you can quickly feel overwhelmed by technical jargon, Python libraries, or statistical models. With this course, my goal is to make this exciting discipline understandable and accessible to everyone, even without advanced mathematical training or computer science background. I offer step-by-step support based on practical experience, concrete projects, and a supportive teaching approach. You'll learn how to manipulate data, extract information from it, and create your first machine learning models with ease. 🎯 Course objectives Discover the basic tools of Data Science with Python Understand and apply the fundamental concepts of exploratory statistics Know how to manipulate, clean, visualize and interpret real data sets Carry out initial predictive modeling (linear regression, classification) 📚 Course content ✔ Fundamental libraries in Data Science – pandas: reading, cleaning and transforming data – numpy: mathematical operations and array manipulation – matplotlib & seaborn: clear and aesthetic data visualization – Getting Started with Scikit-Learn for Machine Learning ✔ Data cleaning and analysis – CSV file import and data mining – Management of missing values and duplicates – Creation of variables, filtering, groupings – Visualization: histograms, curves, heatmaps, boxplots... ✔ Introduction to Machine Learning – Understand how linear and logistic regression work – First classification models (KNN, simple decision trees) – Data separation (training/test set), single cross-validation – Interpretation of results and improvement of the model 🧭 How the sessions work 1️⃣ Assessment of the student's objectives: discovery, professional project, preparation for training, etc. 2️⃣ Personalized progression plan, adapted to the starting level. 3️⃣ Alternation of visual theory and intensive practice on real data sets (health, sports, finance, etc.). 4️⃣ Practical mini-projects at each stage: analyzing survey results, predicting simple results, automating analyses. 5️⃣ Explanation of errors encountered, individualized educational monitoring. 6️⃣ Regular assessment, with reinforcement of key points as needed. 🌐 100% online courses – accessible teaching methods Classes via Zoom, Google Meet, or the tool of your choice Live screen sharing, work on interactive notebook (Jupyter or Google Colab) PDF supports + commented code provided after each session Possibility of intensive coaching for training or an interview Flexible hours, adapted to the time zone of the Gulf countries and your availability 👨‍🎓 For whom? Complete beginners in Data Science and Python Students wishing to enrich their profile with practical skills Professionals retraining for data professions Anyone curious about understanding the world through data! This course has been designed so that each participant can progress at their own pace, develop their analytical logic and discover the pleasure of "making the data speak". Feel free to contact me to discuss your goals and build a customized program together. I would be delighted to accompany you on this wonderful adventure that is data science.
Statistics · Math · Numerical analysis
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Our students from Hanwella Ihala evaluate their Statistics teacher.

To ensure the quality of our Statistics teachers, we ask our students from Hanwella Ihala to review them.
Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.6 out of 5 based on 35 reviews.

Data science , Analytics, Machin learning, statistics
Srinivas
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Srinivas is a skilled tutor. He is patient and has a problem-solving attitude. Shriniva's goal is that students master the subject. An excellent tutor for someone that wants to work hard and become independant user.
Review by IFI
Statistics, Econometrics (including calibration of models on real data) (Adliswil)
Gianmarco
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Gianmarco helped me understand and solve my problems in a friendly, quick and clear manner. He displayed a thorough understanding of the topic. I very much appreciate him as a teacher and can recommend him to anyone.
Review by CHRISTINA
Programming and Data Analysis, Matlab, Python, Fortran, SPSS
Nikolaos
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Nikolas is a very depentable tutor with an abudant amount of knowledge in programming. He was very helpful in preparing me for my programming exam and I higly recommend him!
Review by KYRIAKOS

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