Sprache: Englisch
Verlag: Cambridge University Press, 2022
ISBN 10: 1108747442 ISBN 13: 9781108747448
Anbieter: Friends of the Multnomah County Library, Portland, OR, USA
Softcover. Zustand: Good. Clean pages tightly bound.
Sprache: Englisch
Verlag: Cambridge University Press, 2022
ISBN 10: 1108747442 ISBN 13: 9781108747448
Anbieter: Prior Books Ltd, Cheltenham, Vereinigtes Königreich
Erstausgabe
EUR 16,84
Anzahl: 1 verfügbar
In den WarenkorbPaperback. Zustand: Like New. First Edition. In nearly new condition: firm and square with strong joints, no creases. Just a few hardly noticeable rubs or very mild bumps. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price.
Sprache: Englisch
Verlag: Cambridge University Press, 2022
ISBN 10: 1108747442 ISBN 13: 9781108747448
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 40,31
Anzahl: 1 verfügbar
In den WarenkorbZustand: New.
Sprache: Englisch
Verlag: Cambridge University Press, 2022
ISBN 10: 1108747442 ISBN 13: 9781108747448
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 46,33
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Cambridge University Press, 2022
ISBN 10: 1108747442 ISBN 13: 9781108747448
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. 2022. Paperback. . . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Cambridge University Press, 2022
ISBN 10: 1108747442 ISBN 13: 9781108747448
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This compact course is written for the mathematically literate reader who wants to learn to analyze data in a principled fashion. The language of mathematics enables clear exposition that can go quite deep, quite quickly, and naturally supports an axiomatic and inductive approach to data analysis. Starting with a good grounding in probability, the reader moves to statistical inference via topics of great practical importance - simulation and sampling, as well as experimental design and data collection - that are typically displaced from introductory accounts. The core of the book then covers both standard methods and such advanced topics as multiple testing, meta-analysis, and causal inference.