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Loy, Adam; Kuiper, Shonda; Chihara, Laura – Journal of Statistics Education, 2019
This article describes a collaborative project across three institutions to develop, implement, and evaluate a series of tutorials and case studies that highlight fundamental tools of data science--such as visualization, data manipulation, and database usage--that instructors at a wide-range of institutions can incorporate into existing statistics…
Descriptors: Undergraduate Study, Data Collection, Data Analysis, Statistics
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Johnson, Roger W.; Kliche, Donna V.; Smith, Paul L. – Journal of Statistics Education, 2015
Being able to characterize the size of raindrops is useful in a number of fields including meteorology, hydrology, agriculture and telecommunications. Associated with this article are data sets containing surface (i.e. ground-level) measurements of raindrop size from two different instruments and two different geographical locations. Students may…
Descriptors: Data Analysis, Meteorology, Weather, Measurement Techniques
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Ella Hartenian; Nicholas J. Horton – Journal of Statistics Education, 2015
The Rail Trail and Property Values dataset includes information on a set of n = 104 homes which sold in Northampton, Massachusetts in 2007. The dataset provides house information (square footage, acreage, number of bedrooms, etc.), price estimates (from Zillow.com) at four time points, location, distance from a rail trail in the community, biking…
Descriptors: Statistics, Physical Activities, Parks, Real Estate
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Carter, Nancy; Felton, Nathan; Schwertman, Neil – Journal of Statistics Education, 2014
Engaging students in active learning can enhance their understanding and appreciation of a subject such as statistics. Classroom activities and projects help to engage students and further promote the learning process. In this paper, an activity investigating the influence of population size and wealth on the medal counts from the 2012 London…
Descriptors: Class Activities, Demography, Athletics, Awards
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Matson, Jack E.; Huguenard, Brian R. – Journal of Statistics Education, 2007
The data for 104 software projects is used to develop a linear regression model that uses function points (a measure of software project size) to predict development effort. The data set is particularly interesting in that it violates several of the assumptions required of a linear model; but when the data are transformed, the data set satisfies…
Descriptors: Regression (Statistics), Models, Computer Software, Evaluation