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    Moodle is an open-source Learning Management System (LMS) that provides educators with the tools and features to create and manage online courses. It allows educators to organize course materials, create quizzes and assignments, host discussion forums, and track student progress. Moodle is highly flexible and can be customized to meet the specific needs of different institutions and learning environments.

    Moodle supports both synchronous and asynchronous learning environments, enabling educators to host live webinars, video conferences, and chat sessions, as well as providing a variety of tools that support self-paced learning, including videos, interactive quizzes, and discussion forums. The platform also integrates with other tools and systems, such as Google Apps and plagiarism detection software, to provide a seamless learning experience.

    Moodle is widely used in educational institutions, including universities, K-12 schools, and corporate training programs. It is well-suited to online and blended learning environments and distance education programs. Additionally, Moodle's accessibility features make it a popular choice for learners with disabilities, ensuring that courses are inclusive and accessible to all learners.

    The Moodle community is an active group of users, developers, and educators who contribute to the platform's development and improvement. The community provides support, resources, and documentation for users, as well as a forum for sharing ideas and best practices. Moodle releases regular updates and improvements, ensuring that the platform remains up-to-date with the latest technologies and best practices.

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Available courses

Introduction to Statistics

Introduction to Statistics provides trainees with a foundational understanding of how data are collected, analyzed, interpreted, and communicated. The course emphasizes statistical thinking, real-world applications, and ethical data use. Trainees will learn to summarize data, explore relationships, make predictions, and draw conclusions using both descriptive and inferential statistical methods. Practical examples and hands-on activities help students build confidence in using statistics to inform decisions across academic, professional, and everyday contexts.

Learning Outcomes

By the end of this course, trainees will be able to:

  1. Explain key statistical concepts, terminology, and principles.

  2. Collect data.

  3. Summarize data using tables, graphs, and numerical measures.

  4. Interpret  data using measures of central tendency and variability.

  5. Apply basic probability concepts to real-world situations.

  6. Conduct introductory inferential procedures (e.g., confidence intervals and hypothesis tests).

  7. Analyze relationships between variables using correlation and simple regression.

  8. Use statistical software or calculators to analyze data accurately.

  9. Critically evaluate statistical claims in media and research.

  10. Communicate statistical findings clearly using appropriate visualizations and language.

Sample Interactive Activities

  • Data in Your Life: Students collect a small dataset from their daily routines (e.g., screen time, commute duration) and analyze it using descriptive statistics.

  • Graph Match-Up: Learners match real datasets to the most appropriate graphical displays and explain their choices.

  • Probability Simulations: Interactive simulations (coins, dice, random generators) to explore probability, randomness, and long-run behavior.

  • Stat in the News: Group discussion analyzing statistics used in news articles, advertisements, or social media posts.

  • Hypothesis Testing Lab: Students work in pairs to test a simple claim using real or simulated data.

  • Think-Pair-Share: Short conceptual questions posed during lessons to encourage discussion and clarify misconceptions.

  • Mini Projects: Small group projects where students pose a question, collect data, analyze results, and present findings.