確率・統計の学習・教授<br>The Learning and Teaching of Statistics and Probability : A Perspective Rooted in Quantitative Reasoning and Conceptual Coherence

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確率・統計の学習・教授
The Learning and Teaching of Statistics and Probability : A Perspective Rooted in Quantitative Reasoning and Conceptual Coherence

  • 著者名:Saldanha, Luis/Hatfield, Neil J./Chernoff, Egan J/Primi, Caterina
  • 価格 ¥8,809 (本体¥8,009)
  • Routledge(2023/12/01発売)
  • 春うらら!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~3/15)
  • ポイント 2,400pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9780367654863
  • eISBN:9781003805595

ファイル: /

Description

Filled with practical learning activities to adopt within your classroom, The Learning and Teaching of Statistics and Probability places reasoning about quantities and quantification at the core of learning and teaching statistics. A companion website to this book is also available at https://neilhatfield.github.io/IMPACT_Statistics/, allowing readers to access a directory of resources – data collections and web-based applets – used in some of the instructional activities featured within this book.

Through its presentation of conceptual analyses and resources for teaching with statistical data, the book’s five chapters establish key concepts and foundational ideas in statistics and probability, emphasizing the development of learner understanding and coherence, for example:

  • Individual cases and their attributes
  • Data collections, sub-collections, and relevant operations to quantify their attributes
  • Samples, population, and quantifying variation
  • Types of processes, meanings of randomness, and probability as a measure of stochastic tendency
  • Sampling distributions and statistical inference.

This highly informative yet practical book is an indispensable resource for teachers of secondary school mathematics, mathematics subject leads, and mathematics and statistics educators within the wider field of education.

Table of Contents

Introduction; 1. Individual Cases, Attributes, and Data; 2. Collections of Cases, Attributes of Collections, and Measures of Such Attributes; 3. Samples, Populations, and Quantifying their Variation; 4. Processes, Randomness, and Probability; 5. Sampling Distributions and Statistical Inference; Appendix; Index

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