150,95 €
150,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
75 °P sammeln
150,95 €
150,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
75 °P sammeln
Als Download kaufen
150,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
75 °P sammeln
Jetzt verschenken
150,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
75 °P sammeln
  • Format: ePub

An Introduction to the Bootstrap arms scientists, engineers, and statisticians with the computational techniques they need to analyze and understand complicated data sets. The bootstrap is a computer-based method of statistical inference that answers statistical questions without formulas and gives a direct appreciation of variance, bias, coverage, and other probabilistic phenomena. This book presents an overview of the bootstrap and related methods for assessing statistical accuracy, concentrating on the ideas rather than their mathematical justification. Not just for beginners, the…mehr

  • Geräte: eReader
  • ohne Kopierschutz
  • eBook Hilfe
  • Größe: 3.83MB
Produktbeschreibung
An Introduction to the Bootstrap arms scientists, engineers, and statisticians with the computational techniques they need to analyze and understand complicated data sets. The bootstrap is a computer-based method of statistical inference that answers statistical questions without formulas and gives a direct appreciation of variance, bias, coverage, and other probabilistic phenomena. This book presents an overview of the bootstrap and related methods for assessing statistical accuracy, concentrating on the ideas rather than their mathematical justification. Not just for beginners, the presentation starts off slowly, but builds in both scope and depth to ideas that are quite sophisticated.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Bradley Efron, Department of Statistics Stanford University and Robert J. Tibshirani, Department of Preventative Medicine and Biostatistics and Department of Statistics, University of Toronto.