Probability & Statistics | Al-Azhar University

About This Course

Probability & Statistics is a comprehensive academic course designed for Computer Science students at Al-Azhar University. The course provides a strong foundation in statistical analysis and probability theory, combining essential concepts with detailed, step-by-step problem solving. Throughout the course, students will learn how to understand, analyze, and interpret data using fundamental statistical methods. The course covers descriptive statistics, measures of central tendency, measures of dispersion, probability, sample spaces, events, counting techniques, conditional probability, independent events, multiplication and addition rules, total probability, and Bayes' theorem. The course is structured to help students move from fundamental concepts to more challenging applications, with a strong focus on understanding the logic behind each formula rather than memorizing formulas only. By the end of the course, students will be able to: Understand fundamental statistical and probability concepts. Analyze and summarize different types of data. Calculate and interpret Mean, Median, and Mode. Calculate and interpret Range, Quartile Deviation, Variance, and Standard Deviation. Use the Coefficient of Variation to compare data variability. Construct and analyze sample spaces and events. Apply counting principles and combinations to probability problems. Solve probability problems using addition and multiplication rules. Calculate conditional probabilities correctly. Determine whether events are independent or mutually exclusive. Apply the Law of Total Probability. Solve real-world probability problems using Bayes' Theorem. Approach exam problems systematically and show complete solution steps. The course is designed with a practical, exam-oriented approach while maintaining a strong conceptual foundation, making it suitable for students preparing for university exams and building their foundation for Data Science, Artificial Intelligence, and Machine Learning.

Course Curriculum