This course is designed for first-year LMD Mathematics students who possess a foundational understanding of probability and statistics from their secondary education. It aims to reinforce and build upon these foundations by introducing essential concepts in both descriptive statistics and elementary probability theory, which are fundamental for further studies in mathematics, data analysis, and statistical modeling.
The course is structured into two main parts:
1. Descriptive Statistics: This part provides a comprehensive review of the basic concepts of descriptive statistics. Students will learn to summarize and describe the main features of a data set through both graphical and numerical methods. Topics include:
- Types of data (qualitative vs quantitative).
- Frequency distributions and tables.
- Graphical representations (histograms, bar charts, pie charts, etc.)
- Measures of central tendency (mean, median, mode, etc.)
- Measures of dispersion (range, variance, standard deviation, interquartile range, etc.)
2. Probability calculus: The second part of the course introduces the fundamental principles of probability theory. The focus will be on:
- Basic combinatorial analysis (permutations, combinations, and arrangements).
- Understanding of random experiments, sample spaces, and events.
- Definitions and properties of probability.
- Techniques for computing the probabilities of compound events.
- Introduction to measurable spaces and conditional probabilities.
- Teacher: ismail Boudjema