I’m beginning to do some scenario planning on what will data and statistical services offered by the library look like in 10-15 years. As part of that activity I’m compiling a list of articles, websites,\u00a0&\u00a0presentations that will help inform that perspective.<\/p>\n
Many of these come from the article Teaching the next generation of statistics students to ‘think with data’: special issue on statistics and the undergraduate curriculum<\/a><\/em> by Nicholas Horton and Johanna Hardin. That article has a nice section of key articles on statistics in the undergraduate curriculum, from which I’ve made some selections below.<\/p>\n Setting the stage for data science: integration of data management skills in introductory and second courses in statistics<\/a>. Horton, Baumer, Wickham. 2015. (pdf)<\/p>\n Identifies 5 key elements that deserve greater emphasis in the undergrad curriculum:<\/p>\n The article goes onto illustrate examples of utilizing these 5 elements in coursework.<\/p>\n <\/p>\n Tidy Data<\/a> – slides of presentation by Wickham<\/p>\n Data acquisition and preprocessing in studies on humans: what is not taught in statistics classes?<\/a><\/p>\n Statistics and Science: A Report of the London Workshop on the Future of the Statistical Sciences<\/a> 2014 (pdf)<\/p>\n Humanities Data in R<\/a><\/p>\n Implications of the Data Revolution for Statistics Education<\/a>\u00a0(pdf) 2015 calls for more emphasis on big data, data visualization, and developing an “aesthetic for data handling and modeling based on solving practical problems”.<\/p>\n A data science course for undergraduates: thinking with data<\/a> (pdf)<\/p>\n A cognitive interpretation of data analysis<\/a><\/p>\n Teaching and learning data visualization: ideas and assignments<\/a> (pdf) 2015<\/p>\n\n