SPSS, AMOS. PLS SEM and Research Guidance - Interactive learning

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From 53 C$ /h

I aim equips students and researchers with the essential skills to conduct advanced quantitative research using industry-standard software and statistical methods. Emphasis is placed on data analysis, structural equation modeling, and applied research design, with a focus on interpreting results and applying them in academic and professional contexts.

Learning Focus

SPSS (Statistical Package for the Social Sciences):
Data preparation, descriptive statistics, reliability testing, regression, ANOVA, and hypothesis testing.

AMOS (Analysis of Moment Structures):
Confirmatory factor analysis (CFA), measurement model testing, structural equation modeling (SEM), and model fit assessment.

PLS-SEM (Partial Least Squares Structural Equation Modeling):
Application of SmartPLS or WarpPLS for predictive modeling, higher-order constructs, mediation/moderation analysis, and validation techniques (AVE, CR, HTMT).

Research Guidance:
Understanding research design, formulating hypotheses, structuring a thesis, interpreting outputs, reporting results in APA style, and preparing manuscripts for conferences or journals.

Extra information

download SPSS or AMOS

Location

Online from Bahrain

Age

Adults (18-64 years old)

Student level

Beginner

Intermediate

Advanced

Duration

60 minutes

The class is taught in

Arabic

English

Skills

Numerical analysis

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

Adobe software package (Photoshop, Illustrator, InDesign, Motion graphic)

67 C$ /h

This course introduces students to the Adobe Creative Cloud package, focusing on industry-standard tools used in graphic design, multimedia production, and visual communication. Through a hands-on, project-based approach, students will gain foundational skills in Adobe Photoshop, Illustrator, and InDesign while exploring how these applications integrate to support professional design workflows.

Students will learn to:

Use Adobe Photoshop for image editing, photo manipulation, and digital compositing.

Apply Adobe Illustrator for creating vector-based graphics, logos, and illustrations.

Design and publish layouts in Adobe InDesign, such as posters, brochures, and magazines.

Understand file formats, color modes (RGB/CMYK), typography, and prepress requirements.

Develop creative projects that combine multiple applications, simulating real-world design tasks.

Dimitri

5.0

(2)

Microsoft Excel is very powerful data analysis software. It is a practical solution in the short to medium and long term to automate your calculations, to have a global and detailed overview on your activities, and to analyze your data.

As an accountant, marketer, commercial agent, secretary, merchant, salesperson or company manager, a good mastery of this software will improve your efficiency, your competitiveness, and will save you a lot of time and money. Whatever your field of activity, this software is designed to help you.

During this training you will learn:
- best practices, functionalities and tools;
- functions and their use;
- handling of Dynamic Cross Tables, dynamic graphics,
- the design of dashboards,
- and you will acquire reflexes that will be useful for your entire career.

Duration of training: 1 month
Number of hours: 24 hours

I am expecting many of you because we have a lot to share.

Yas

5.0

(2)

With years of experience as an engineer in Belgium and the Netherlands, I would like to help other students navigate the sometimes complex world of mathematics and physics. During my studies, I tutored for six years in secondary schools in the regions of The Hague, Delft, Rotterdam, and Antwerp. In doing so, I aim to review the subject matter interactively with the student and link theoretical concepts as much as possible to examples from our daily lives to prepare and motivate the student.

So if you would like tutoring on one or more subjects in mathematics or physics, you can contact me.

Mohamed

5.0

(2)

As an experienced math teacher, I offer private math lessons via webcam, math tutoring to catch up on gaps, as well as intensive math lessons before exams. I specialize in helping middle school/high school students with math homework and I offer distance math lessons tailored to the student's needs. My goal is to help you improve your math skills quickly and effectively prepare for the baccalaureate/brevet. I also listen to students experiencing academic difficulties and can offer you personalized support to overcome your difficulties.

Middle school or high school students from the French mission. The 2nd and 1st general Terminale specialty classes of the French system
The 5th, 4th and 3rd levels of the college
levels T and Common Core Sciences, Technological TC, 1st Baccalaureate Experimental Sciences and final year of all streams (SVT-PC-SC.Math)
My goal is to help students to:

Improve their level
Deepen their knowledge
Assimilate their courses
fill in their gaps
improve
I am also able to support them in preparing for their exams and competitive entrance exams to the grandes écoles, as well as provide them with homework help. I am convinced that I have the qualities required to enable my students to progress and perhaps even give them a taste for this subject!
I am considered one of the best online math tutors. I also offer math support for French mission students and math help for international students wishing to follow the French curriculum.
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"Private math tutor for [level] (e.g. middle school, high school, 3rd, final year)"
"Math lessons at home"
“Math help for struggling students”
"Math lessons to improve grades"
“Preparation for the brevet/baccalaureate in mathematics”
"Online math teacher for [level]"
"Cheap math tutoring"
"Personalized online math lessons"
“Find a certified math teacher”

Mohamed

5.0

(2)

An exam is coming up and your child doesn't know where to start? Is the Baccalaureate or Brevet exam approaching and they lack method or confidence?
He knows the material but loses his composure when faced with an exercise?
He makes repetitive mistakes despite his revisions?
He doesn't know how to organize his revision?
There isn't enough time to review all the chapters?
Or does he simply want to prepare himself seriously to achieve better results?
I can help him organize his work, target his difficulties and train effectively.
I am a mathematics teacher with 15 years of teaching experience and hold a Master's degree in mathematics. I tutor middle and high school students, particularly in the French and Moroccan curricula.
🎯 Preparation tailored to the student's objective
Good preparation is not just about doing a lot of exercises.
First, we need to identify:
• concepts that are not mastered;
• errors that recur regularly;
• methods that the student does not yet know how to use;
• the priority chapters;
• the actual level of preparation.
Next, we implement a targeted and progressive approach.
📝 Preparation for tests and exams
Depending on the level and objective, we can work on:
• review of essential concepts;
• classic exercises and more complex exercises;
• the exam topics;
• problems requiring multiple steps of reasoning;
• the problem-solving methodology;
• drafting the solutions;
• time management;
• the analysis and correction of errors;
• the strategies to use when faced with different types of exercises.
For the Brevet or the Baccalaureate, we can also work from past exam papers to gradually familiarize the student with the exam format.
🔎 A method based on errors
An error is not simply something to be corrected.
It allows us to understand what is not yet mastered.
During the sessions, we therefore analyze the errors to determine their origin, then we repeat the method until the student is able to solve a similar exercise independently.
Understand → Practice → Identify errors → Correct → Repeat → Master
💻 Interactive online courses
The classes are held remotely using Google Meet and an interactive whiteboard.
The student works directly with me during the session. It's not simply a matter of looking at a solution: they must search, explain their reasoning and participate actively.
I can also send him screenshots of the work done during the session to facilitate revisions.
🏆 15 years of experience
I have worked with many students of varying levels and difficulties.
For my final year students who were tutored in mathematics, I achieved a 100% success rate in the Baccalaureate, with 75% obtaining a distinction of "Bien" or "Très Bien".
This experience allows me to adapt the work to the available time and the actual level of the student, especially when an exam is approaching.
👨‍🎓 For which students?
• College
• High school
• Second
• First
• Final year
• Preparation for the Brevet exam
• Preparation for the Baccalaureate
• Preparation for inspections
• Students needing a refresher course before an exam
The French and Moroccan programs are taken into account.
📩 An exam is coming up?
In your message, please tell me:
• the student's level;
• the type of examination or test;
• the date;
• the relevant chapters;
• the main difficulties encountered.
This will allow me to determine priorities and propose work that is adapted to the time available.
The goal is to prepare the student effectively, to correct their priority difficulties and to enable them to approach their exam with more method and confidence.

Medo

5.0

(2)

As a highly qualified maths teacher, a graduate of the college of teachers and with 11 years of teaching experience in public high schools, I am happy to offer tutoring lessons in mathematics at home for students from level T and Common Core Sciences, TC Technological, 1st Baccalaureate Experimental Sciences and final of all the sectors (SVT-PC-SC.Math-L), as well as for the classes of 2nd and 1st general, Terminale specialty of the French system, as well than the 5th, 4th and 3rd levels of college.

My primary objective is to help students improve their level, deepen their knowledge, assimilate their lessons, fill their gaps and improve their skills in the discipline of mathematics. In addition, I am perfectly able to support them in the preparation of their exams and competitions for access to the Grandes Ecoles, and to provide them with homework help so that they can succeed in this subject.

With my advanced math skills and knowledge, I am confident that I can provide my students with effective tools and techniques to help them progress. My goal is to give them confidence and help them develop a passion for mathematics, a subject that can seem daunting at first, but can be exciting and rewarding if taught in an interesting and fun way.

By choosing my tutoring courses in mathematics, students can expect to receive individual attention and personalized help to overcome their difficulties and achieve their goals. My teaching approach is interactive and student-centered, which allows for a deeper understanding of mathematical concepts and a more practical application of acquired knowledge.

In summary, I am confident in my skills as a math teacher to help students of all levels progress and succeed in this demanding subject. I am convinced that my dynamic and stimulating teaching methods will help my students achieve their math goals and build a confidence that will follow them throughout their lives.

Kevin

5.0

(2)

► 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.

Aafaq

5.0

(2)

Calculus I, the first course in this extensive mathematics curriculum, teaches students the foundational ideas of limits, derivatives, and how to apply them to real-world issues including rates of change and optimization. Calculus III, which builds on this basis, introduces partial derivatives, multiple integrals, and vector calculus, extending these concepts into several dimensions. When taken as a whole, these calculus courses build the solid analytical foundation and spatial thinking abilities needed for further study in applied mathematics, science, and engineering.

Students study Number Theory concurrently, exploring the complex patterns and characteristics of integers, such as primes, modular arithmetic, divisibility, and the classical theorems that form the basis of much of contemporary computer science and encryption. In addition to this theoretical emphasis, the Numerical Methods course gives students useful computational tools to help them approximate solutions to challenging mathematical problems that are impossible to solve analytically. Students are prepared for a variety of jobs in mathematics, engineering, technology, and other fields by this program, which blends strong theoretical knowledge with algorithmic problem-solving abilities.

Alessandro

5.0

(2)

Hey there! Alessandro here - I am a PhD student in Atmospheric Sciences with a background in Chemistry and Environmental Sciences. I will be happy to help you with mathematics, numerical (and data) analysis and statistics, from the basics to university level. If you have questions for me, feel free to reach out!

- ITA -
Ehi! Sono Alessandro, un dottorando in scienze dell'atmosfera con un percorso di studi tra chimica e scienze ambientali. Sarò felice di aiutarti in matematica, analisi, analisi dati e statistica, dalle basi fino ai livelli più avanzati. Se hai domande da farmi, manda pure un messaggio!

Aqsa

5.0

(2)

This lesson builds a solid foundation in numbers and variables by helping students understand how numbers are represented, how variables are used to express unknown values, and how they relate to real-world situations. Through clear explanations, guided examples, and practice activities, students develop algebraic thinking, logical reasoning, and confidence needed for advanced mathematics.

Daniel

5.0

(2)

The lesson is tailored to your wishes. I can explain the theory from the *Getal & Ruimte* method (or *Moderne Mathematics*). We can go through the exercises you want to review, or simply the exercises in the book. We can review tests or prepare for exams. Together, we will strive for mathematics that you understand.

Karim

5.0

(2)

Are you an engineering or mathematics (Bachelor's/Master's) student who finds numerical analysis too abstract or difficult to apply?

This course provides a rigorous yet practical introduction to scientific computing, showing how numerical methods are used to solve real engineering and scientific problems.
You'll first learn how numerical computations behave by studying floating-point arithmetic, rounding and truncation errors, conditioning, stability, and error propagation. These concepts are essential for understanding why numerical algorithms succeed—or fail.
Next, you'll learn how to solve nonlinear equations using the bisection method, fixed-point iteration, and Newton's method, before moving on to linear systems through both direct methods (Gaussian elimination, LU decomposition, Cholesky factorization) and iterative methods (Jacobi, Gauss-Seidel, and relaxation methods).
The second half of the course covers polynomial interpolation and approximation (Lagrange, Newton, Hermite, least-squares approximation, and splines), numerical differentiation and integration, and numerical methods for ordinary differential equations, including Euler's method, Runge-Kutta methods, and finite difference techniques.
Every algorithm is implemented step by step in Matlab so that you not only understand the mathematics behind it but also learn how to apply it to practical engineering problems. Throughout the course, we compare the accuracy, convergence, stability, and computational efficiency of the different numerical methods.
This course is ideal for students preparing for university exams, engineering projects, scientific computing courses, or anyone wishing to build solid foundations in numerical analysis.

Prerequisites: A good understanding of single-variable calculus, basic linear algebra, and elementary programming concepts is recommended.

Bouchouata

5.0

(2)

I am a mathematics teacher with university teaching experience. Holding a Master's degree and a State Engineering diploma, I support pupils and students in their mathematics learning with a clear, progressive method adapted to their level.
I propose private lessons for:
Middle School
High school
University students (Bachelor's degree)
I can help you in the following areas:
Algebra
Analysis
Differential and integral calculus
Differential equations
Statistics
Probabilities
Exam preparation and resits
My goal is to help you understand essential concepts, improve your study methods, and gain confidence. Each session is tailored to the student's needs, with clear explanations, progressive exercises, and detailed feedback.
Courses can be taught in French or English, online or in person depending on availability.

Jude

5.0

(2)

My lessons are designed to take you from simply following code to genuinely understanding how data science works.

We can cover the complete data science process, including data cleaning, exploratory data analysis, feature engineering, visualisation, statistics, machine learning, model evaluation and communicating results.

Depending on your goals, lessons can include:

Python, pandas, NumPy and scikit-learn
Data cleaning and exploratory analysis
Regression and classification
Decision trees, random forests and boosting
Clustering and dimensionality reduction
Cross-validation and model evaluation
Feature engineering and model interpretation
Neural networks and deep learning foundations
Bayesian modelling and PyMC
Portfolio and interview preparation
Support understanding university modules and projects

I use diagrams, analogies and practical demonstrations to make difficult ideas easier to understand. We will normally begin with an intuitive explanation, look at the underlying logic or mathematics, and then implement the concept in Python.

Lessons are personalised around your level. Complete beginners receive a structured learning path, while experienced students can focus on advanced topics, project guidance, debugging or interview preparation.

You will be encouraged to explain ideas back to me, interpret results and make your own modelling decisions. My goal is not only to help you produce working code, but to help you become an independent and confident data scientist.

Adel

5.0

(2)

List of lessons

1. Vector Spaces & Subspaces
Key concepts: Understanding the definition of vector space and the ten conditions (Vector Space Axioms) to prove that a set with addition and multiplication operations in its standard form a vector space.
Linear Independence & Dependence: Testing whether vectors are linearly independent or dependent on each other.
Span, Basis & Dimension:
Determine the generative span of the space.
Finding the basis and dimension of different spaces (such as vector spaces \mathbb{R}^n, matrices M_{m \times n}, and polynomials P_n).
Subspaces: Subspace conditions, finding the null space, column space, and row space of matrices.
2. Linear Transformations and Applications
Definition and properties: Proving the linearity of applications and determining the Standard Matrix Representation.
Kernel and Range:
Calculate the kernel (Kernel/Null Space) and image (Image/Range) for conversion.
Applying the Rank-Nullity Theorem and calculating rank and nihilism.
Change of Basis: Transition Matrices and how to represent the same linear transformation under different bases and families.
3. Eigenvalues & Eigenvectors
Characteristic Equation: Finding the eigenvalues of \lambda by solving the equation \det(A - \lambda I) = 0.
Eigenvectors and Eigenspaces: Finding the eigenspace associated with each eigenvalue by solving the homogeneous system (A - \lambda I)\vec{v} = \mathbf{0}.
Diagonalization:
Diagonalizability Condition Test.
Formulating the decomposition of diagonal A = PDP^{-1} to facilitate the calculation of matrix powers A^k and the solving of systems of differential equations.
Orthogonal Diagonalization: For symmetric matrices and the application of Spectral Theorem.

Jayaram

5.0

(2)

Overview

Transitioning from learning data science theory to solving actual business problems is the hardest step for any aspiring data professional. [Insert Chosen Course Title] is an intensive, mentor-led program designed to simulate a real-world data team environment. Instead of working through synthetic, pre-cleaned textbook datasets, you will take on messy, complex industry scenarios and turn them into end-to-end data products.

What You’ll Experience

End-to-End Execution: Walk through the full data lifecycle—from problem scoping and data extraction to exploratory analysis, modeling, and executive stakeholder presentation.

Industry-Standard Workflows: Work with messy real-world datasets, practice Git-based version control, write production-ready code, and structure reports that business leaders actually care about.

1-on-1 & Group Mentorship: Receive continuous code reviews, architectural feedback, and project guidance mirroring the experience of working under a Senior Data Scientist or Analytics Lead.

Portfolio-Ready Deliverables: Graduate with 2–3 complete, polished projects that demonstrate actual business value to hiring managers—not just another churn prediction copy-pasted from Kaggle.

Who This Is For
Aspiring Data Analysts, Data Scientists, and recent graduates who know Python, but want the practical experience, confidence, and portfolio needed to land high-impact roles in the industry.