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This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
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Since November 2021
Instructor since November 2021
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Programming, mathematics, linguistics courses
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From 26 € /h
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Student in the research course in Computer Science Linguistics at the University of Paris, I have a background in literature through a license and in mathematics with a CPGE. My goal during private lessons is to explain the lessons with a different vision of a traditional teacher and to train the student not only for his homework and exams but also for the rest of his course.
Location
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At student's location :
  • Around Vitry-sur-Seine, France
About Me
Student in Computer Linguistics at the University of Paris but also passionate about literature and more particularly imaginary novels. Thanks to my natural curiosity towards science and letters, I was able to acquire a number of skills in these fields. With a specialization in computer science, I also learned several programming and web development languages, to orient myself towards Automatic Language Processing.

Since elementary school, I have in mind the idea of becoming a teacher, in college, then in high school until today where my course takes me to the profession of teacher-researcher. As a student, I realize the difficulties that students can have in understanding and learning their lessons and therefore, I have more facilities to understand why the student does not understand certain passages and how to make him assimilate the course despite that. I like dynamic and motivated students to learn lessons, even creative, especially in programming. I adapt easily to the profile of the student, if he likes to go further or if he is only looking to succeed in his year.
Education
Baccalaureate S with very good mention and European mention
MPSI, obtained with equivalences
L1 and L2 of Letters, major of promotion
L3 of Computer Linguistics, research course
Experience / Qualifications
Private math teacher for a final year student
Explanation of lessons and daycare for primary school children
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Duration
30 minutes
45 minutes
60 minutes
90 minutes
120 minutes
The class is taught in
French
English
Availability of a typical week
(GMT -04:00)
New York
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At student's home
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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Amine
◾ Tools

R studio • SQL • SPSS • SAS • Jamovi • JASP

◾ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

◾ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL
- Descriptive, exploratory and multivariate statistical analyses on business data
- Production of performance indicators and actionable analyses to support decision-making

◾ Selection and implementation of methods

- Preparation and structuring of databases
- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)
- Linear and logistic regressions
- Factor analyses (PCA / MCA)
- Mediation and moderation models
- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics
- Help in understanding and interpreting the results
- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)
- Multivariate analyses
- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)
- t-tests (one and two samples, independent or paired)
- Chi-square, binomial tests
- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)
- Logistic regression
- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA
- Repeated measures ANOVA
- Fixed and random effects
- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)
- Exploratory factor analysis
- Factorial rotations
- Validation and interpretation of structures and clusters

◾ Reporting & communication

- Clear, structured and concise reporting of results
- Visualizations tailored to decision-makers
- Support for strategic and operational decision-making
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Contact Mathilde
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1st lesson is backed
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Similar classes
arrow icon previousarrow icon next
verified badge
Amine
◾ Tools

R studio • SQL • SPSS • SAS • Jamovi • JASP

◾ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

◾ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL
- Descriptive, exploratory and multivariate statistical analyses on business data
- Production of performance indicators and actionable analyses to support decision-making

◾ Selection and implementation of methods

- Preparation and structuring of databases
- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)
- Linear and logistic regressions
- Factor analyses (PCA / MCA)
- Mediation and moderation models
- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics
- Help in understanding and interpreting the results
- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)
- Multivariate analyses
- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)
- t-tests (one and two samples, independent or paired)
- Chi-square, binomial tests
- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)
- Logistic regression
- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA
- Repeated measures ANOVA
- Fixed and random effects
- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)
- Exploratory factor analysis
- Factorial rotations
- Validation and interpretation of structures and clusters

◾ Reporting & communication

- Clear, structured and concise reporting of results
- Visualizations tailored to decision-makers
- Support for strategic and operational decision-making
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