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Statistical Methods and Applications from a Historical Perspective
. Ed(S): Mignani, Stefania; Crescenzi, Fabio
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Description for Statistical Methods and Applications from a Historical Perspective
Editor(s): Mignani, Stefania; Crescenzi, Fabio. Series: Studies in Theoretical and Applied Statistics / Selected Papers of the Statistical Societies. Num Pages: 417 pages, 12 black & white illustrations, 46 colour illustrations, biography. BIC Classification: GPS; JHBC. Category: (P) Professional & Vocational. Dimension: 241 x 166 x 27. Weight in Grams: 768.
The book showcases a selection of peer-reviewed papers, the preliminary versions of which were presented at a conference held 11-13 June 2011 in Bologna and organized jointly by the Italian Statistical Society (SIS), the Institute national Institute of Statistics (ISTAT) and the Bank of Italy. The theme of the conference was "Statistics in the 150 years of the Unification of Italy."
The celebration of the anniversary of Italian unification provided the opportunity to examine and discuss the methodological aspects and applications from a historical perspective and both from a national and international point of view. The critical discussion on the ... Read more
Show LessProduct Details
Publication date
2014
Publisher
Springer International Publishing AG Switzerland
Number of pages
426
Condition
New
Series
Studies in Theoretical and Applied Statistics / Selected Papers of the Statistical Societies
Number of Pages
414
Format
Hardback
Place of Publication
Cham, Switzerland
ISBN
9783319055510
SKU
V9783319055510
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About . Ed(S): Mignani, Stefania; Crescenzi, Fabio
Fabio Crescenzi is an expert highly skilled in issues related to survey methodology. He works at the National Institute of Statistics as head of the Office for statistical methods in the Department of Census and registers. Stefania Mignani is a Full Professor of Statistics at University of Bologna. Her research interests focus on methodological developments in latent variable models ... Read more
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