Luca Lista is full professor at University of Naples Federico II and Director of INFN Naples Unit. He is an experimental particle physicist and member of the CMS collaboration at CERN. He participated in the BABAR experiment at SLAC and L3 experiment at CERN. His main scientific interests are data analysis, statistical methods applied to physics and software development for scientific applications.

"The most unique selling point of this text is that it is highly illustrative, including many colourful and insightful figures which aides in the dissemination of the material presented. ... this textbook is written with particle physics applications in mind, the text is still easily accessible to readers with backgrounds across the physical sciences. ... this text offers an insightful viewpoint of how analyses are carried at experiments in the modern age." (physicsbookreviewer.blogspot.com, January 29, 2024) “The book is important because, as AI and data science continue to shape the future, much interdisciplinary work is being done in many different domains. It is a very good example of interdisciplinary physics research using AI and data science. ... Graduate students are often expected to apply theoretical knowledge. This book will be an invaluable resource for them, to jumpstart their research by getting equipped with the right statistical and data analysis toolsets.” (Gulustan Dogan, Computing Reviews, August 8, 2023)

• Introduction to Probability and Inference.- Discrete Probability Distributions.- Probability Density Functions.- Random Numbers and Monte Carlo Methods.- Bayesian Probability and Inference.- Frequentist Probability and Inference.- Combining Measurements.- Confidence Intervals.- Convolution and Unfolding.- Hypothesis Testing.- Machine Learning.- Discoveries and Limits.

Luca Lista is full professor at University of Naples Federico II and Director of INFN Naples Unit. He is an experimental particle physicist and member of the CMS collaboration at CERN. He participated in the BABAR experiment at SLAC and L3 experiment at CERN. His main scientific interests are data analysis, statistical methods applied to physics and software development for scientific applications.

"The most unique selling point of this text is that it is highly illustrative, including many colourful and insightful figures which aides in the dissemination of the material presented. ... this textbook is written with particle physics applications in mind, the text is still easily accessible to readers with backgrounds across the physical sciences. ... this text offers an insightful viewpoint of how analyses are carried at experiments in the modern age." (physicsbookreviewer.blogspot.com, January 29, 2024) “The book is important because, as AI and data science continue to shape the future, much interdisciplinary work is being done in many different domains. It is a very good example of interdisciplinary physics research using AI and data science. ... Graduate students are often expected to apply theoretical knowledge. This book will be an invaluable resource for them, to jumpstart their research by getting equipped with the right statistical and data analysis toolsets.” (Gulustan Dogan, Computing Reviews, August 8, 2023)

• Introduction to Probability and Inference.- Discrete Probability Distributions.- Probability Density Functions.- Random Numbers and Monte Carlo Methods.- Bayesian Probability and Inference.- Frequentist Probability and Inference.- Combining Measurements.- Confidence Intervals.- Convolution and Unfolding.- Hypothesis Testing.- Machine Learning.- Discoveries and Limits.