211 citations · 571 across the 18 of their papers we have counts for
18 papers
How learners produce data from text in classifying clickbait
Nicholas J. Horton, Jie Chao, Phebe Palmer +1
Text provides a compelling example of unstructured data that can be used to motivate and explore classification problems. Challenges arise regarding the representation of features…
Data science transfer pathways from associate's to bachelor's programs
Benjamin S. Baumer, Nicholas J. Horton
A substantial fraction of students who complete their college education at a public university in the United States begin their journey at one of the 935 public two-year colleges.…
Fostering better coding practices for data scientists
Randall Pruim, Maria-Cristiana Gîrjău, Nicholas J. Horton
Many data science students and practitioners don't see the value in making time to learn and adopt good coding practices as long as the code "works". However, code standards are an…
Spam four ways: Making sense of text data
Nicholas J. Horton, Jie Chao, William Finzer +1
The world is full of text data, yet text analytics has not traditionally played a large part in statistics education. We consider four different ways to provide students with oppor…
An educator's perspective of the tidyverse
Mine Çetinkaya-Rundel, Johanna Hardin, Benjamin S. Baumer +3
Computing makes up a large and growing component of data science and statistics courses. Many of those courses, especially when taught by faculty who are statisticians by training,…
Facilitating team-based data science: lessons learned from the DSC-WAV project
Chelsey Legacy, Andrew Zieffler, Benjamin S. Baumer +2
While coursework provides undergraduate data science students with some relevant analytic skills, many are not given the rich experiences with data and computing they need to be su…
Integrating computing in the statistics and data science curriculum: Creative structures, novel skills and habits, and ways to teach computational thinking
Nicholas J. Horton, Johanna S. Hardin
Nolan and Temple Lang (2010) argued for the fundamental role of computing in the statistics curriculum. In the intervening decade the statistics education community has acknowledge…
Implementing version control with Git and GitHub as a learning objective in statistics and data science courses
Matthew D. Beckman, Mine Çetinkaya-Rundel, Nicholas J. Horton +3
A version control system records changes to a file or set of files over time so that changes can be tracked and specific versions of a file can be recalled later. As such, it is an…
Greater data science at baccalaureate institutions
Amelia McNamara, Nicholas J. Horton, Benjamin S. Baumer
Donoho's JCGS (in press) paper is a spirited call to action for statisticians, who he points out are losing ground in the field of data science by refusing to accept that data scie…
Updated guidelines, updated curriculum: The GAISE College Report and introductory statistics for the modern student
Beverly L. Wood, Megan Mocko, Michelle Everson +2
Since the 2005 American Statistical Association's (ASA) endorsement of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report, changes in the…
A mean score method for sensitivity analysis to departures from the missing at random assumption in randomised trials
Ian R. White, James Carpenter, Nicholas J. Horton
Most analyses of randomised trials with incomplete outcomes make untestable assumptions and should therefore be subjected to sensitivity analyses. However, methods for sensitivity…
Enriching students' conceptual understanding of confidence intervals: An interactive trivia-based classroom activity
Xiaofei Wang, Nicholas G. Reich, Nicholas J. Horton
Confidence intervals provide a way to determine plausible values for a population parameter. They are omnipresent in research articles involving statistical analyses. Appropriately…
Challenges and opportunities for statistics and statistical education: looking back, looking forward
Nicholas Jon Horton
The 175th anniversary of the ASA provides an opportunity to look back into the past and peer into the future. What led our forebears to found the association? What commonalities do…
Data Science in Statistics Curricula: Preparing Students to "Think with Data"
Johanna Hardin, Roger Hoerl, Nicholas J. Horton +1
A growing number of students are completing undergraduate degrees in statistics and entering the workforce as data analysts. In these positions, they are expected to understand how…
R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics
Ben Baumer, Mine Cetinkaya-Rundel, Andrew Bray +2
Nolan and Temple Lang argue that "the ability to express statistical computations is an essential skill." A key related capacity is the ability to conduct and present data analysis…
Teaching precursors to data science in introductory and second courses in statistics
Nicholas J Horton, Benjamin S Baumer, Hadley Wickham
Statistics students need to develop the capacity to make sense of the staggering amount of information collected in our increasingly data-centered world. Data science is an importa…
Adjusting models of ordered multinomial outcomes for nonignorable nonresponse in the occupational employment statistics survey
Nicholas J. Horton, Daniell Toth, Polly Phipps
An establishment's average wage, computed from administrative wage data, has been found to be related to occupational wages. These occupational wages are a primary outcome variable…
I hear, I forget. I do, I understand: a modified Moore-method mathematical statistics course
Nicholas Jon Horton
Moore introduced a method for graduate mathematics instruction that consisted primarily of individual student work on challenging proofs (Jones, 1977). Cohen (1982) described an ad…