Curriculum Guidelines for Undergraduate Programs in Statistical Science
The American Statistical Association endorses the value of
undergraduate programs in statistics as a reflection of the increasing
importance of the discipline. We expect statistics programs to provide
sufficient background in the following core skill areas: statistical
methods and theory, data management, computation, mathematical
foundations, and statistical practice. Statistics programs should be
flexible enough to prepare bachelor's graduates to either be functioning
statisticians or go on to graduate school.
The widely cited McKinsey report states that "by 2018, the United
States alone could face a shortage of 140,000 to 190,000 people with
deep analytical skills as well as 1.5 million managers and analysts
with the know-how to use the analysis of big data to make effective
decisions". A large number of those will be at the bachelor's level.
The number of bachelor's graduates in statistics has increased by more
than 140% since 2003 (21% from 2012 to 2013).
Much has changed since the previous guidelines were disseminated in
2000. The 2014 guidelines reflect changes in curriculum and suggested
pedagogy. Institutions need to ensure that students entering the
workforce or heading to graduate school have the appropriate capacity to
"think with data" and to pose and answer statistical questions.
Key points include:
Increased importance of data science: Working with data
requires extensive computing skills. To be prepared for statistics and
data science careers, students need facility with professional
statistical analysis software, the ability to access and manipulate
data in various ways, and the ability to perform algorithmic
problem-solving. In addition to more traditional mathematical and
statistical skills, students should be fluent in higher-level
programming languages and facile with database systems.
Real applications: Data should be a major component of
statistics courses. Programs should emphasize concepts and approaches
for working with complex data and provide experiences in designing
studies and analyzing non-textbook data.
More diverse models and approaches: Students require
exposure to and practice with a variety of predictive and explanatory
models in addition to methods for model building and assessment. They
must be able to understand issues of design, confounding, and bias.
They need to know how to apply their knowledge of theoretical
foundations to the sound analysis of data.
Ability to communicate: Students need to be able to
communicate complex statistical methods in basic terms to managers and
other audiences and to visualize results in an accessible manner. They
must have a clear understanding of ethical standards. Programs should
provide multiple opportunities to practice and refine these statistical
practice skills.
These guidelines are intended to be flexible while ensuring that
programs provide students with the appropriate background along with
necessary critical thinking and problem-solving skills to thrive in our
increasingly data-centric world. Programs are encouraged to be creative
with their curriculum to provide a synthesis of theory, methods,
computation, and applications.
2014 Curriculum Guidelines for Undergraduate Programs in Statistical Science (PDF Format)
These guidelines were endorsed by the Board of Directors of the
American Statistical Association on November 15, 2014. The new
guidelines are now available here. Feedback can be sent to Rebecca Nichols, Director of Education, at [email protected].
The appropriate citation for the 2014 guidelines is:
American Statistical Association Undergraduate Guidelines Workgroup. 2014. 2014 curriculum guidelines for undergraduate programs in statistical science. Alexandria, VA: American Statistical Association.
A special issue of the American Statistician on "statistics and the undergraduate curriculum" has been published (November, 2015). The table of contents and link to articles can be found at http://www.tandfonline.com/toc/utas20/69/4.
White Papers
Resources
2013-2014 Webinar Series on Undergraduate Statistics
2000 Curriculum Guidelines for Undergraduate Programs in Statistical Science