Statistics and Analysis of Scientific Data

The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains.

Features new to this edition include:

- a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets.
- a new chapter on the various measures of the mean including logarithmic averages.
- new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors.
- a new case study and additional worked examples.
- mathematical derivations and theoretical background material have been appropriately marked, to improve the readability of the text.
- end-of-chapter summary boxes, for easy reference.

As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.

A doua editie revizuita a acestui manual ofera cititorului o baza solida in teoria probabilitatii si statisticile aplicate stiintelor fizice, ingineriei si domeniilor conexe. Acesta acopera o gama larga de metode numerice si analitice care sunt esentiale pentru analiza corecta a datelor stiintifice, inclusiv teoria probabilitatii, functiile de distributie a statisticilor, se potriveste cu datele bidimensionale si estimarea parametrilor, metodele Monte Carlo si lanturile Markov. aceasta editie include: - o discutie despre tehnicile statistice utilizate in stiinta afacerilor, cum ar fi analiza regresiei multiple a seturilor de date multivariate. - un nou capitol despre diferitele masuri ale mediei, inclusiv medii logaritmice. cu privire la potrivirea datelor cu erori bivariate. - un nou studiu de caz si exemple suplimentare lucrate. - derivarile matematice si materialele teoretice de fundal au fost marcate in mod corespunzator, pentru a imbunatati lizibilitatea textului. Ca si in prima editie, principala metoda pedagogica este o abordare teorie-apoi-aplicativa, unde se pune accentul pe fi Mai intai pe o intelegere solida a teoriei care sta la baza unui subiect, care devine baza pentru o aplicare eficienta si practica a materialului.