Ammar - Statistics tutor - Montréal
1st lesson free
Ammar - Statistics tutor - Montréal

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Ammar will be happy to arrange your first Statistics lesson.

Ammar

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Ammar will be happy to arrange your first Statistics lesson.

  • Rate R345
  • Response 2h
  • Students

    Number of students Ammar has accompanied since joining Superprof

    50+

    Number of students Ammar has accompanied since joining Superprof

Ammar - Statistics tutor - Montréal
  • 5 (55 reviews)

R345/h

1st lesson free

Contact

1st lesson free

1st lesson free

  • Statistics
  • Mathematical analysis
  • Forensic Science
  • SPSS

Master Statistics, Probability, Data Analysis, and Econometrics using SPSS, R, Stata, SAS, and Power BI with a PhD Engineer and Professor | 25+ Years’ Expertise | Students, Researchers and Professiona

  • Statistics
  • Mathematical analysis
  • Forensic Science
  • SPSS

Lesson location

Ambassador

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Ammar will be happy to arrange your first Statistics lesson.

About Ammar

I am a multidisciplinary educator, researcher, engineer, trainer, and consultant with more than 25 years of experience in research, statistical analysis, professional training, and applied problem solving.
My academic background includes a Bachelor’s degree in Engineering, a Master’s degree in Management Information Systems, and a PhD in Knowledge Management and Artificial Intelligence. This combination allows me to connect statistical theory with research, technology, business, engineering, health sciences, psychology, education, and other applied fields.
Over the years, I have completed hundreds of statistical and research projects and supported or supervised hundreds of university learners and researchers working on theses, dissertations, and applied studies. I am experienced in translating complex technical ideas into clear, structured explanations and practical decisions.
For Statistics specifically, I combine conceptual teaching with hands-on analysis using tools such as SPSS, R, Stata, SAS, JASP, and Jamovi. I focus on method selection, assumptions, diagnostics, interpretation, and communication - not merely on obtaining software output.
I teach in English, French, and Arabic and adapt my explanations to the learner’s background, level, profession, and goals.

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About the lesson

  • Primary
  • Secondary
  • Matric/GCSE
  • +7
  • levels :

    Primary

    Secondary

    Matric/GCSE

    BTech

    Adult education

    Masters

    MBA

    AS Level

    A Level

    Doctorate

  • French
  • English

Languages in which the lesson is available :

French

English

Statistics should not be reduced to formulas, software menus, or isolated calculations. My lessons are designed to help you understand the statistical reasoning behind each method, select the correct technique, perform the analysis accurately, interpret the results critically, and communicate your conclusions with confidence.

I teach school, college, university, graduate, doctoral, MBA, and professional learners. Each lesson is adapted to your level, field, dataset, assignment, research question, thesis, dissertation, examination, or workplace project.

Depending on your objectives, lessons may cover:
• Data preparation and quality control, including data cleaning, variable coding, missing-data handling, outlier assessment, transformations, dataset restructuring, and data merging.
• Descriptive statistics, probability distributions, sampling methods, confidence intervals, statistical inference, and hypothesis testing.
• Research and study design, including experimental, observational, and survey-based studies; variable operationalization; sampling strategies; and the alignment of research questions, hypotheses, variables, and statistical methods.
• Effect sizes, statistical power, sample-size determination, and power analysis using G*Power when appropriate.
• Correlation and regression analysis, including simple and multiple linear regression, logistic regression, ordinal and multinomial regression, Poisson and negative-binomial regression, and model diagnostics.
• Analysis of variance, including ANOVA, ANCOVA, MANOVA, repeated-measures designs, mixed designs, post-hoc comparisons, and interaction effects.
• Categorical-data analysis and nonparametric methods, including chi-square tests, contingency tables, Mann–Whitney, Wilcoxon, Kruskal–Wallis, and related procedures.
• Generalized linear models, mixed-effects models, multilevel modelling, and introductory survival analysis when required.
• Applied econometrics, including cross-sectional and panel-data models, fixed and random effects, endogeneity, instrumental variables, difference-in-differences, model specification, and cautious causal interpretation.
• Time-series analysis and forecasting, including trend, seasonality, stationarity, autocorrelation, decomposition, exponential smoothing, ARIMA foundations, residual diagnostics, forecast accuracy, and time-series validation.
• Multivariate analysis, principal component analysis, exploratory and confirmatory factor analysis, reliability and scale assessment, structural equation modelling foundations, mediation, moderation, and moderated mediation.

Software support may include SPSS, R and RStudio, Stata, SAS, JASP, Jamovi, Excel, G*Power, EViews, and Minitab. When appropriate, I can also support statistical workflows using Python and Jupyter Notebook, as well as reproducible reporting with R Markdown or Quarto.

Access, SQL, Power BI, and Tableau may also be incorporated when they are needed for data preparation, extraction, visualization, or communication within a broader statistical or research workflow.

My teaching emphasizes understanding rather than mechanical software use. You will learn:
• Why a method is appropriate—or inappropriate—for your data
• How to verify assumptions and diagnose statistical problems
• How to interpret coefficients, significance levels, confidence intervals, effect sizes, and model performance
• How to distinguish statistical significance from practical importance
• How to recognize limitations, uncertainty, bias, and misleading conclusions
• How to report results clearly in academic or professional language, including APA-style reporting when required

When useful, lessons may include annotated software output, worked examples, practice questions, concise notes, reusable syntax or code, publication-quality tables and figures, and a structured analysis plan that you can apply independently after the session.

Whether you need to understand a difficult concept, prepare for an examination, analyze a real dataset, select the correct methodology, troubleshoot an existing model, or present defensible research results, the lesson will be structured around your actual objective and the standards of your discipline.

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Rates

Rate

  • R345

Package rates

  • 5h: R1724
  • 10h: R3448

online

  • R345/h

travel

  • + R10

free lesson

The free first lesson with Ammar allows you to get to know the tutor and discuss your needs and expectations.

  • 1h

Details

Getting started: You may begin directly with a paid tutoring session when the topic and objective are already clear. If you prefer to discuss your needs first, we can have a brief free Zoom meeting - together with a parent or guardian when relevant - to clarify the level, goals, and best learning plan. No booking or payment is required for this introductory meeting;

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