Resource Library

As our economy, society, and daily life become increasingly dependent on data, work across nearly all fields is becoming more data driven, affecting both the jobs that are available and the skills that are required. At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine were asked to set forth a vision for the emerging discipline of data science at the undergraduate level. The study committee considered the core principles and skills undergraduates should learn and discussed the pedagogical issues that must be addressed to build effective data science education programs. Data Science for Undergraduates: Opportunities and Options underscores the importance of preparing undergraduates for a data-enabled world and recommends that academic institutions and other stakeholders take steps to meet the evolving data science needs of students. 

Watch the report release webinar here:  https://vimeo.com/269033724  

The app allows you to see the trade-offs on various types of outlier/anomaly detection algorithms. Outliers are marked with a star and cluster centers with an X.

One of the original (and still best) sources for archived data.

Gapminder seeks to educate all on the importance of "factfulness" and of knowing and contextualizing the statistics that describe the state of our world.  These data sets provide facts from across the globe such as average income, life expectancy, energy use, education levels, and much more.

Gapminder seeks to educate all on the importance of "factfulness" and of knowing and contextualizing the statistics that describe the state of our world.  Learn facts from across the globe such as average income, life expectancy, energy use, education levels, and much more.

Download Gapminder’s slides, tools, posters, handouts, lesson plans, and presentations at this webpage.

Gapminder seeks to educate all on the importance of "factfulness" and of knowing and contextualizing the statistics that describe the state of our world.  Learn facts from across the globe such as average income, life expectancy, energy use, education levels, and much more.

This particular page gives teachers resources to use in their classrooms involving the tools and data found on Gapminder.

Gapminder seeks to educate all on the importance of "factfulness" and of knowing and contextualizing the statistics that describe the state of our world.  Learn facts from across the globe such as average income, life expectancy, energy use, education levels, and much more.

CATS, established in 1978, promotes the statistical sciences, statistical education, statistics applications, and related issues affecting the statistics community. The mission and scope of CATS evolved over time as interdisciplinary collaboration increasingly shaped the character of scientific research. After a brief hiatus, CATS was reconstituted in 2011 and has since focused on improving the visibility and practice of statistics within government agencies not well connected to statistics, increasing attention to statistical issues of big data and data science, and helping agencies identify bottlenecks impairing their analysis capabilities. Its multidisciplinary members are experts from statistics and related fields and leaders in diverse areas of interdisciplinary research, including the analysis of large-scale data, computational biology and bioinformatics, spatial data, environmental science, neuroscience, health care policy, and complex computer experiments.

This is the free online textbook for the Foundations of Data Science class at UC Berkeley for the Data 8 Project. Creators have used https://github.com/data-8/textbook to maintain this textbook (an open source project that allows for continual easy editing and maintenance).

This site offers separate webpages about statistical topics relevant to those studying psychology such as research design, representing data with graphs, hypothesis testing, and many more elementary statistics concepts.  Homework problems are provided for each section.