Dr Vijay Reena - Data Analysis tutor - Kensington
Dr Vijay Reena - Data Analysis tutor - Kensington

Dr Vijay Reena's profile, diploma and contact details have been verified by our experts

Dr Vijay Reena

  • Rate 701 GHS
  • Response 13h
  • Students

    Number of students Dr Vijay Reena has accompanied since arriving at Superprof

    39

    Number of students Dr Vijay Reena has accompanied since arriving at Superprof

Dr Vijay Reena - Data Analysis tutor - Kensington
  • 5 (6 reviews)

701 GHS/hr

Contact
  • Data Analysis

Experienced in critically analyzing the data and their interpretations. Clinical and basic research

  • Data Analysis

Lesson location

Super Prof

Dr Vijay Reena is one of our best Data analysis tutors. They have a high-quality profile, verified qualifications, a quick response time, and great reviews from students!

About Dr Vijay Reena

Teaching data analysis to undergraduate and master's level students isn't just about conveying information; it's about nurturing a passion for discovery and problem-solving. As an educator, my aim is to empower students with the analytical skills and knowledge they need to thrive in their academic pursuits and future careers. By sharing my enthusiasm for data analysis and facilitating meaningful learning experiences, I aspire to inspire the next generation of researchers, analysts, and decision-makers. Teaching isn't just a profession; it's a calling driven by the desire to make a positive impact and contribute to the intellectual growth and development of others.

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About the lesson

  • Primary school
  • Junior high school
  • SHS 1
  • +14
  • levels :

    Primary school

    Junior high school

    SHS 1

    SHS 2

    BTS

    Adult Education

    Facultate (Licență)

    Master's degree

    Higher national diploma

    Doctor of philosophy

    Pre school

    Beginner

    Intermediate

    Advanced

    Professionel

    Others

    Child

  • English

All languages in which the lesson is available :

English

Mean, median, mode, variance, standard deviation and inferential statistics (probability distributions, hypothesis testing, confidence intervals). Ensure that students have a solid understanding of these concepts before moving on to more advanced topics.

Data Exploration Techniques: Introduce students to techniques for exploring datasets, including data visualization methods such as histograms, box plots, scatter plots, and correlation matrices. Emphasize the importance of data visualization in gaining insights and identifying patterns in data.

Statistical Methods: Teach a variety of statistical methods commonly used in data analysis, such as regression analysis, analysis of variance (ANOVA), t-tests, chi-square tests, and non-parametric tests. Explain when and how to apply each method based on the type of data and research questions.

Discuss principles of experimental design and sampling techniques to ensure the validity and reliability of data analysis results. Teach students how to design experiments, choose appropriate sample sizes, and control for confounding variables to minimize bias and increase the robustness of statistical analyses.

Interpretation and Communication: Emphasize the importance of interpreting statistical results in the context of the research question and drawing meaningful conclusions. Teach students how to effectively communicate their findings through written reports, presentations, and data visualization tools to different stakeholders.

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Rates

Rate

  • 701 GHS

Pack prices

  • 5h: 3,388 GHS
  • 10h: 6,696 GHS

online

  • GHS701/h

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