Introduction to Series and Basic Statistics
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About this ebook
The theoretical assumptions of the following mathematical topics are presented in this book:
numerical successions
numerical series
combinatorial calculus
elementary statistics
Each topic is treated by emphasizing practical applications and solving some significant exercises.
Simone Malacrida
Simone Malacrida (1977) Ha lavorato nel settore della ricerca (ottica e nanotecnologie) e, in seguito, in quello industriale-impiantistico, in particolare nel Power, nell'Oil&Gas e nelle infrastrutture. E' interessato a problematiche finanziarie ed energetiche. Ha pubblicato un primo ciclo di 21 libri principali (10 divulgativi e didattici e 11 romanzi) + 91 manuali didattici derivati. Un secondo ciclo, sempre di 21 libri, è in corso di elaborazione e sviluppo.
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Introduction to Series and Basic Statistics - Simone Malacrida
Introduction to Series and Basic Statistics
SIMONE MALACRIDA
The theoretical assumptions of the following mathematical topics are presented in this book:
numerical successions
numerical series
combinatorial calculus
elementary statistics
Each topic is treated by emphasizing practical applications and solving some significant exercises.
––––––––
Simone Malacrida (1977)
Engineer and writer, has worked on research, finance, energy policy and industrial plants.
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ANALYTICAL INDEX
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INTRODUCTION
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I – SUCCESSION AND SERIES
Successions
Series: Definitions
Notable series
Applications
Exercises
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II – COMBINATORY CALCULATION
Definitions
Operations
Applications
Exercises
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III – ELEMENTARY STATISTICS
Chance
Conditional probability and Bayes' theorem
Elementary statistics
Applications
Exercises
INTRODUCTION
This book focuses on two distinct topics.
On the one hand, numerical sequences and series are presented, as a fundamental basis for understanding developments related to mathematical analysis (such as function series and power series).
On the other hand, combinatorial calculus with elements of elementary statistics is introduced.
This second part is the prerequisite for understanding statistics, stochastic laws and probability distributions, topics that require academic analytical knowledge and which,