STATISTICS

Statistics provides learners with a rigorous foundation in statistical thinking and data analysis. The course introduces measures of location and spread, including mean, median, mode, range, interquartile range, variance, and standard deviation, enabling students to summarize and interpret data effectively. Learners also develop skills in representing data using tables, histograms, cumulative frequency curves, box-and-whisker plots, and scatter diagrams, with emphasis on clear interpretation. Core concepts of probability are covered through theoretical and experimental approaches, including mutually exclusive events, combined probabilities, and basic probability laws. The course further explores correlation and regression, focusing on identifying relationships between variables using scatter diagrams, interpreting correlation coefficients, and applying linear regression for prediction. Finally, students are introduced to the normal distribution, learning its key properties, standardisation using z-scores, and applications in solving real-life statistical problems, equipping them with analytical skills essential for further study and practical decision-making.

 
 

Probability and Statistics

Course Title: Probability and Statistics

Course Description:
This course introduces students to the fundamental concepts of probability and statistics and their applications in real-world situations. It covers basic probability principles, random variables, probability distributions, sampling techniques, data presentation, and statistical inference. Students will learn how to collect, organize, analyze, and interpret data to make informed decisions. The course emphasizes both theoretical understanding and practical application using examples from various fields.

Learning Outcomes:
By the end of the course, students should be able to:

  1. Explain key concepts of probability and statistics.

  2. Apply probability rules and distributions to solve practical problems.

  3. Organize and summarize data using descriptive statistics.

  4. Perform statistical analysis using measures of central tendency and dispersion.

  5. Use sampling methods and hypothesis testing to make data-driven decisions.

  6. Interpret and communicate statistical results effectively.

Probability

This course introduces the fundamental concepts and techniques of probability theory, providing a foundation for statistical reasoning and data analysis. Students will explore probability models, random variables, probability distributions, expectation, variance, and key theorems such as the Law of Large Numbers and the Central Limit Theorem. Emphasis is placed on applying probability to real-world situations and developing problem-solving skills relevant to fields such as science, engineering, and business.