“It is better to be approximately right than precisely wrong.”

John Maynard Keynes (1883-1946) British economist


Statistics as a key to understanding the world of data

Imagine finding yourself faced with a sea of complex and seemingly chaotic data: company sales, results of scientific experiments, market trends, to name a few. Statistics acts like a magnifying glass, transforming this apparent chaos into a clear and understandable vision. It is the key that unlocks the information potential of each piece of data, allowing us to extract meaning, draw conclusions and make informed decisions.

Marginal Probability charts

Statistics offers the tools to describe, accurately and synthetically, the essential characteristics of a set of data. Centrality measures such as the mean, median, and mode provide an indication of central tendency, while dispersion measures such as the standard deviation tell us how much the data deviates from the mean. This information is critical to understanding the structure and variability of the data we are exploring.

python logo
R Logo

Descriptive Statistics and Inferential Statistics

The Allure of the Unknown: The Continuous Evolution of Statistics

Statistics, in all its charm, is destined to evolve. The modern era sees the emergence of machine learning techniques, which integrate advanced statistical approaches to emerge complex patterns from data. This fusion of disciplines promises to bring statistics to face more complex challenges, guiding us through the ever-growing labyrinth of digital data.

In conclusion, the fundamentals of statistics are an intrinsic link in understanding and interpreting our data-driven world. Descriptive Statistics paints the picture, Inferential Statistics guides us on our journey. With the addition of perspectives such as Bayesian Statistics and Non-Parametric Statistics, our conceptual arsenal is enriched, preparing us to face the challenges of the future and unravel new mysteries through numerical analysis.