Real Estate Mathematics
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Course Detail

Real Estate Mathematics

This course equips learners with the essential mathematical skills needed for property valuation, financial calculations, and real estate transactions. It enables learners to accurately perform calculations related to interest rates, commissions, mortgages, and other key real estate financial concepts.
Real Estate Mathematics Unit Standards

7468 - Mathematical Literacy for Further Education and Training

This unit standard is intended for individuals seeking recognition at Further Education and Training levels or fulfilling fundamental NQF requirements. It covers the application of mathematics in financial instruments, interest calculations, cost and revenue analysis, and economic debates.

  • Using mathematics to plan and control financial instruments such as insurance, unit trusts, and bonds.
  • Applying simple and compound interest in contexts including mortgages and annuities.
  • Investigating costs, revenue, marginal analysis, and profit optimisation.
  • Using mathematics to discuss economic topics like tax and productivity.

9016 - Mathematical Literacy at NQF Level 4

This unit standard aims to develop confident mathematical literacy relevant to everyday life and occupational experiences. It encourages critical awareness of mathematics' role in society and enhances problem-solving skills in practical and geometrical contexts.

  • Measuring, estimating, and calculating physical quantities for practical use.
  • Exploring and solving problems using two and three-dimensional geometry.
  • Applying mathematical insight to manage everyday and workplace needs.

9015 - Data Handling and Probability at NQF Level 4

This unit standard focuses on data collection, organization, and statistical problem solving using probability models. Learners develop critical thinking skills to interpret and apply probability and statistics in real-world decision making.

  • Critiquing and using techniques for data collection and representation.
  • Applying theoretical and experimental probability to build models and make predictions.
  • Using statistical models to solve problems and support decision making.
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