
05595718
j
2009e.00204
Konold, Cliff
Kazak, Sibel
Reconnecting data and chance.
Technol. Innov. Stat. Educ. 2, No. 1, 37 p., electronic only (2008).
2008
California Digital Library (CDL), University of California, Oakland, CA; University of California, Los Angeles (UCLA), Department of Statistics, Los Angeles, CA
EN
D30
K40
K50
K60
distribution
data modeling
exploratory data analysis
computer modeling
law of large numbers, measurement error
model fit
probability
signalnoise
sample space
variation
Summary: For the past 15 years, preuniversity students in many countries including the United States have encountered data analysis and probability as separate, mostly independent strands. Classroombased research suggests, however, that some of the difficulties students have in learning basic skills in Exploratory Data Analysis stem from a lack of rudimentary ideas in probability. We describe a recent project that is developing materials to support middleschool students in coming to see the ``data in chance" and the ``chance in data." Instruction focuses on four main ideas: model fit, distribution, signalnoise, and the Law of Large Numbers. Central to our approach is a new modeling and simulation capability that we are building into a future version of the dataanalysis software TinkerPlots. We describe three classroomtested probability investigations that employ an iterative modelfit process in which students evaluate successive theories by collecting and analyzing data. As distribution features become a focal point of students' explorations, signal and noise components of data become visible as variation around an ``expected'' distribution in repeated samples. An important part of students' learning experience, and one enhanced through visual aspects of TinkerPlots, is becoming able to see things in data they were previously unable to see.