R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…

National College Access Network (NCAN) has heard repeatedly and consistently over the years that one of the best aspects of network membership is the ability to collaborate with and learn from other members. In an effort to further the transfer of ideas, in the summer of 2016 NCAN hosted a series of four Idea Incubators across the country, which…

The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…

Data analysis methods, both numerical and visual, are used to discover a variety of surprising patterns in the errors associated with successive approximations to the derivatives of sinusoidal and exponential functions based on the Newton difference-quotient. L'Hopital's rule and Taylor polynomial approximations are then used to explain why these…

In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of…

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

Conducting labs isn't a new way to teach physics, but labs have become increasingly prevalent with the rise of inquiry. Physics students collect mostly quantitative data, often represented by graphs or tables. Interpreting this data can be a challenge for students, especially when it comes to experimental error. To address this issue, this article…

This article characterizes and measures errors in the 2010 National Research Council (NRC) assessment of research-doctorate programs in geography. This article provides a conceptual model for data-based sources of uncertainty and reports on a quantitative assessment of NRC research data uncertainty for a particular geography doctoral program.…

The 2012 edition of the "Digest of Education Statistics" is the 48th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…

The 2011 edition of the "Digest of Education Statistics" is the 47th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…

This paper summarizes an experiment conducted to examine the counting performance of 7- and 8-year-olds. Analysis of variance was computed on counting errors produced when enumerating a set of squares on a computer screen. The factors included in the analysis were age, gender, array size, error type, proximity, and error form. The primary…

Error profiles for the Fall Enrollment Survey of the Higher Education General Information Survey (HEGIS) were developed as part of an assessment of the quality of survey data. Three statistics were of particular interest: the count of full-time equivalent students, the breakdown by race/ethnicity, and the count of unclassified students. Attention…

Maintains that there is an inconsistency in the regression analysis of the data presented in Maureen J. Lage and Michael Treglia's 1996 article, "The Impact of Integrating Scholarship on Women into Introductory Economics." The authors admit the error, correct it, and report no difference in their original conclusions. (MJP)