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Teaching Statistics and Quantitative Methods in the 21st Century is a guide for rethinking and revitalising statistics and quantitative methods pedagogy for both novice and experienced instructors at undergraduate and graduate levels. It offers modern, transformative approaches to preparing students as future researchers.
Now in its second edition, this ground-breaking volume tackles the question of how introductory statistics and quantitative methods should be taught, drawing on contributions from highly accomplished teachers. Many current textbooks and syllabi remain little changed from those used half a century ago, despite major developments in the field and its role in research. The book rests on a core principle: introductory teaching should open the pathway to advanced training and equip students to become accomplished researchers.
New chapters address:
The role of Artificial Intelligence in teaching statistics Classroom software applications and applets Automated homework generation and grading Teaching the replication crisis New treatments of p-values, null hypothesis significance testing, and abduction A pedagogical approach based on statistical modelling rather than hypothesis testing
Updated and expanded chapters from the first edition sit alongside these new contributions, presenting both classroom innovations and philosophical challenges to the status quo. The result is a call for a broad reimagining of how statistics and quantitative methods are introduced, designed to engage students, support new instructors, and renew the practice of seasoned teachers
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Teaching Statistics and Quantitative Methods in the 21st Century is a guide for rethinking and revitalising statistics and quantitative methods pedagogy for both novice and experienced instructors at undergraduate and graduate levels. It offers modern, transformative approaches to preparing students as future researchers.
Now in its second edition, this ground-breaking volume tackles the question of how introductory statistics and quantitative methods should be taught, drawing on contributions from highly accomplished teachers. Many current textbooks and syllabi remain little changed from those used half a century ago, despite major developments in the field and its role in research. The book rests on a core principle: introductory teaching should open the pathway to advanced training and equip students to become accomplished researchers.
New chapters address:
The role of Artificial Intelligence in teaching statistics Classroom software applications and applets Automated homework generation and grading Teaching the replication crisis New treatments of p-values, null hypothesis significance testing, and abduction A pedagogical approach based on statistical modelling rather than hypothesis testing
Updated and expanded chapters from the first edition sit alongside these new contributions, presenting both classroom innovations and philosophical challenges to the status quo. The result is a call for a broad reimagining of how statistics and quantitative methods are introduced, designed to engage students, support new instructors, and renew the practice of seasoned teachers