This course is designed for second year computer science engineering, it provides them with a strong foundation in
analyzing relationships between two variables and making reliable statistical inferences about populations based on
sample data. Mastering these concepts is essential for interpreting real-world data and making data-driven decisions.
In this course the student will learn:
Bi-Dimensional Descriptive Statistics: Explore how two variables interact using scatter plots, correlation coefficients,
and cross-tabulations.
Summarize joint distributions with covariance, contingency tables, and regression lines. Visualize patterns and detect
trends in paired datasets.
Estimation Theory: Understand the principles of point estimation (e.g., sample mean, MLE) and interval estimation
(confidence intervals).
Evaluate the quality of estimators (bias, efficiency, consistency). Apply estimation techniques to real-world problems,
accounting for uncertainty.
- Enseignant: Tayeb BOUAZIZ