What Makes a Good Statistical Question?

Autor/inn/en	Arnold, Pip; Franklin, Christine
Titel	What Makes a Good Statistical Question?
Quelle	In: Journal of Statistics and Data Science Education, 29 (2021) 1, S.122-130 (9 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
DOI	10.1080/26939169.2021.1877582
Schlagwörter	Statistics Education; Problem Solving; Data Collection; Data Analysis; Data Interpretation; Investigations; Questioning Techniques + Suchen Sie Ihr Suchwort? Problemlösen; Data capture; Datensammlung; Auswertung; Data evaluation; Datenauswertung; Untersuchung; Befragungstechnik; Fragetechnik
Abstract	The statistical problem-solving process is key to the statistics curriculum at the school level, post-secondary, and in statistical practice. The process has four main components: formulate questions, collect data, analyze data, and interpret results. The Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) emphasizes the importance of distinguishing between a question that anticipates a deterministic answer and a question that anticipates an answer based on data that will vary, referred to as a statistical question. This article expands upon the Pre-K-12 GAISE distinction of a statistical question by addressing and identifying the different types of statistical questions used across the four components of the statistical problem-solving process and the importance of interrogating these different statistical question types. Since the publication of the original Pre-K-12 GAISE document, research has helped to clarify the purposes of questioning at each component of the process, to clarify the language of questioning, and to develop criteria for answering the question, "What makes a good statistical question?" (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01