Statistics as unbiased estimators: exploring the teaching of standard deviation. Issue 3 (2nd September 2017)

• Record Type: Journal Article
• Authors: Wasserman, Nicholas H.; Casey, Stephanie; Champion, Joe; Huey, Maryann
• Is Part Of: Research in mathematics education. Volume 19:Issue 3(2017)
• Page Start: 236
• Page End: 256
• Publication Date: 2017-09-02
• Subjects: Standard deviation -- unbiased estimator -- statistical knowledge for teaching; Mathematics -- Study and teaching -- Periodicals; 510.71
• DOI: 10.1080/14794802.2017.1333918
• Languages: English
• ISSNs: 1479-4802

Abstract

ABSTRACT: This manuscript presents findings from a study about the knowledge for and planned teaching of standard deviation. We investigate how understanding variance as an unbiased (inferential) estimator – not just a descriptive statistic for the variation (spread) in data – is related to teachers' instruction regarding standard deviation, particularly around the issue of division by n -1. In this regard, the study contributes to our understanding about how knowledge of mathematics beyond the current instructional level, what we refer to as nonlocal mathematics, becomes important for teaching. The findings indicate that acquired knowledge of nonlocal mathematics can play a role in altering teachers' planned instructional approaches in terms of student activity and cognitive demand in their instruction.