Könyv Archaeological Reasoning Edward (University of Toronto) Banning

Archaeological Reasoning

Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 10-18 napon belül
44 530 Ft
Bridging the gap between introductory and advanced archaeology courses, this book builds confidence...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2026
oldal
240
EAN
9798765157480
Enbook ID
48912720
Súly
503
Méretek
28 x 28 x 28

Teljes leírás

Bridging the gap between introductory and advanced archaeology courses, this book builds confidence in working with the tools of archaeological research and how to make plausible inferences about the past.


How do archaeologists learn what happened thousands of years ago when all they have to work with are clusters of broken artifacts or patterns of post holes? Are their explanations any better than theories about ancient civilizations that we see in social media or popular streaming services? This book answers those questions and more.


Archaeological Reasoning: A Guide to Understanding the Past explains the ways archaeologists draw conclusions from evidence, recognizing that those interpretations will change as new evidence comes into play. Readers will learn more about the research strategies and methods that archaeologists use to understand ancient technologies, economies, social and political systems, and, more specifically, to help them find, date, or classify sites, artifacts, or whole societies. The book also helps them learn to "think statistically" without necessarily doing any statistics, and reinforces skills in map-reading and effective ways to explore data with graphs.

The book is richly illustrated with more than 80 maps, images and diagrams to help students visualize sites and artifacts and understand key concepts.

Archaeological Reasoning includes 12 exercises, with fictitious case studies from around the world and different research traditions. These build students' confidence in how to interpret data, without any expectation of statistical background. Using realistic, messy, but relatively small data sets, these exercises allow readers to think critically about how to draw reasonable conclusions, to appreciate that there may be alternative explanations, and to learn how to make strong, evidence-based arguments to support their own interpretations.

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