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As statistics and data science instructors, we often seek to use data in our courses that are rich, real, realistic, and relevant. To this end we created the fivethirtyeight R package of data and code behind the stories and interactives at the data journalism website FiveThirtyEight.com. After a discussion on the conflicting pedagogical goals of "minimizing prerequisites to research" (Cobb 2015) while at the same time presenting students with a realistic view of data as it exists "in the wild," we articulate how a desired balance between these two goals informed the design of the package. The details behind this balance are articulated as our proposed "Tame data principles for introductory statistics and data science courses." Details of the package's construction and example uses are included as well.

This study reports the importance 244 parents of six-year-old children living in Singapore placed on cognitive (problem-solving and creativity) and non-cognitive (practical school skills and conforming) behaviours. Our research team hypothesised that, as the age of the parent increased, the importance placed on each covariant skill (problem solving, creativity, practical, conformity) would differ. It was further hypothesised that the importance placed on cognitive skills compared with noncognitive skills for six-year-old children would decrease. Our results indicate that, when controlling for demographics, as parents aged they did place different levels of importance on each of the cognitive skills but not the non-cognitive skills. Furthermore, older parents placed less importance on cognitive compared with non-cognitive skills. The gap between average cognitive rating and average non-cognitive scores decreased as parents' age increased. This gap was found to be smaller for Chinese than non-Chinese parents. It decreased with age when controlling for child gender and parent ethnicity, gender and occupation.