Data Analysis as the Search for Signals in Noisy Processes.

By Clifford E. Konold, Alexander Pollatsek. 2002

302 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/391bed8ccd27c92b7ce6f6fe7abc63d4d4e3890d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

1. M. Pfannkuch
2. Dani Ben-Zvi
3. Arthur Bakker
4. K. Makar
5. Joan Garfield
6. Jan Derry
7. Chris Wild
8. Sibel Kazak

Citations in the corpus

• How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics (2007, methodology): “Other contexts where students’ reasoning about variability were examined include variability in a univariate data set (Konold & Pollatsek, 2002; Petrosino et al., 2003; Ben-Zvi, 2004a; Groth, 2005), bivariate relationships (Cobb et al., 2003b; Hammerman & Rubin, 2003), comparing groups (Biehler,…”
• Conceptual Challenges in Coordinating Theoretical and Data-centered Estimates of Probability (2011, background): “…there is evidence from both the history of the development of statistical thinking and from classroom research that suggests that applying, for example, the idea of average as signal across different contexts is not a simple matter (Konold & Pollatsek, 2002; Lehrer & Schauble, 2007).”
• COMPARING BOX PLOT DISTRIBUTIONS: A TEACHER’S REASONING (2006, methodology): “Konold and Pollatsek (2002) note that research has demonstrated that students know how to compute averages but few use averages to characterize a dataset or to make comparisons between datasets.”
• REASONING ABOUT SHAPE AS A PATTERN IN VARIABILITY (2004, methodology): “I call this activity " growing a sample " (following Konold & Pollatsek, 2002), though some readers may prefer to call it " growing a data set.”
• USING DATA COMPARISON TO SUPPORT A FOCUS ON DISTRIBUTION: EXAMINING PRESERVICE TEACHERS’ UNDERSTANDINGS OF DISTRIBUTION WHEN ENGAGED IN STATISTICAL INQUIRY (2006, background): “Unexplained variation in data creates noise and the primary purpose of many statistical techniques is to unearth the signal within the noise (Konold & Pollatsek, 2002; Wild & Pfannkuch, 1999).”
• A FRAMEWORK FOR THINKING ABOUT INFORMAL STATISTICAL INFERENCE (2009, background): “Konold & Pollatsek (2002) articulated this as " a new level of commitment to involve students in the analysis of real data to answer practical questions " (p. 259).”
• Learning to reason from samples (2015, unknown): “Building on this work, Saldanha and Thompson (2002) studied high school students’ reasoning about samples and sampling distributions.”
• Lessons from Inferentialism for Statistics Education (2011, methodology): “The problem situation we used in the 14th period to support students’ statistical reasoning was the fish farmer story, originally designed by Konold and Pollatsek (2002).”
• Development of probabilistic understanding in fourth grade (2016, background): “Konold and Pollatsek (2002) suggested the metaphor of signal in noise, identifying “noise” with variation and “signal” with the expectation or central tendency that can be extracted from the noise.”
• Preservice Elementary Teachers' Conceptual and Procedural Knowledge of Mean, Median, and Mode (2006, background): “Konold and Pollatsek (2002) illustrated the importance of conceptual understanding of averages beyond the idea that they can represent typical values in fixed distributions.”
• STATISTICAL INFERENCE AT WORK: STATISTICAL PROCESS CONTROL AS AN EXAMPLE (2008, background): “What is underlying this is the view that data can be seen as model plus residuals or signal plus noise (Konold & Pollatsek, 2002).”