Competences

• • a)Represent and interpret complex datasets using Venn Diagrams and Tree Diagrams demonstrating a strong grasp of  relationships and probabilities within the data;
  • b)Apply and visualize the Complement and Addition Rules on Venn Diagrams ensuring a comprehensive understanding of probability theory;
  • c)Critically evaluate and select the most appropriate measure of Central Tendency based on the nature and distribution of the dataset;
  • d)Develop curriculum related material to be used to explain probability in the classroom;
  • e)Plan different activities to maximise students’ understanding of probability.

Knowledge

• • • a)Distinguish between discrete and continuous data;
    • b)Distinguish between empirical and theoretical probability;
    • c)List the benefits and drawbacks of both empirical and theoretical probability;
    • d)Describe the meaning of dependent and independent events;
    • e)Identify situations that involve permutations and those that involve combinations;
    • f)Describe the meaning of mathematical expectation, variance and standard deviation;
    • g)Distinguish between the Binomial, Hypergeometric, Poisson and Normal Distributions.
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Skills

• • • a)Apply the formula for Conditional Probability to solve complex problems, demonstrating an ability to identify and analyse dependent events within various mathematical contexts;
    • b)Use the appropriate formulae for permutations and combinations to accurately determine outcomes in both simple and complex scenarios;
    • c)Use binomial coefficients in combinations to solve advanced problems illustrating a thorough understanding of their role in probability theory and algebraic expressions;
    • d)Interpret and analyse a Venn Diagram and a Tree Diagram to extract data and probabilities;
    • e)Work with distribution functions for discrete and continuous random variables applying them to diverse probability models and interpreting their significance in various statistical contexts;
    • f)Apply different Probability Distributions selecting and utilising the appropriate distribution model.