About This Course

Welcome to Introduction to Probability and Descriptive Statistics, a foundational course designed for first-year undergraduate students in Mathematics and Computer Science Applied to the Human and Social Sciences (MIASHS).

This course introduces the fundamental concepts of descriptive statistics and probability, providing the essential tools required to analyze data and model uncertainty. Students will learn how to organize, summarize, visualize, and interpret data using tables, graphs, and key statistical measures such as the mean, median, mode, variance, and standard deviation.

The course also covers the foundations of probability theory, including counting techniques, sample spaces, events, probability rules, conditional probability, Bayes' theorem, and independent events. In addition, students will study the Binomial, Poisson, and Normal distributions, together with their expected values and variances, and will explore basic applications of exploratory data analysis (EDA) using introductory Python tools.

By the end of this course, students will be able to analyze and interpret data, apply probability models to real-world problems, and develop the quantitative reasoning and problem-solving skills required for further studies in mathematics, computer science, engineering, data science, and related fields.

We are delighted to welcome you to this course and wish you a successful and rewarding learning experience.