# Education > Undergraduate Education

## Resources for Department Chairs

**This webpage is maintained by the ASA/MAA Joint Committee on Undergraduate Statistics Education and is intended for mathematics departments that bear primary responsibility for the teaching of statistics at their institutions. It contains information on the following topics:**

- Qualifications for Teaching an Introductory Statistics Course
- Statistics Courses for Mathematics Majors
- Statistics Majors and Minors
- Supporting and Evaluating Statisticians within Mathematics Departments

### 1. Qualifications for Teaching an Introductory Statistics Course

The American Statistical Association (ASA) and the Mathematical Association of America (MAA) have jointly developed recommended qualifications for an instructor teaching a modern introductory statistics course.

In the joint statement titled Qualifications for Teaching an Introductory Statistics Course, the two groups encourage effective teaching in undergraduate statistical education and offer a series of qualifications and resources that will assist non-statistics departments at universities and colleges with hiring qualified candidates or training existing instructors to acquire the necessary skill set.

### 2. Statistics Courses for Mathematics Majors

The **2004 Committee on the Undergraduate Program in Mathematics (CUPM) Guide ^{1}** states: it is more important that mathematics majors study statistics or probability with an approach that is data-driven than one that is calculus-based. The concepts and reasoning needed in a statistics course is different from those needed in mathematics courses. An introductory course should

**(1)**emphasize statistical thinking: the importance of data production; the omnipresence of variability; and the quantification and explanation of variability;

**(2)**place a strong emphasis on data and concepts and less emphasis on theory and recipes; and

**(3)**foster active learning.

^{1}http://www.maa.org/programs/faculty-and-departments/curriculum-department-guidelines-recommendations/cupm/cupm-guide-2004, These guidelines are being rewritten. A new version is expected to appear in 2015 with a similar recommendation.

**What do statistics courses look like?**

In 2000 the symposium, "Improving the Work Force of the Future: Opportunities in Undergraduate Statistics Education" was held to discuss and make recommendations for the future of undergraduate courses and programs in statistics. The following paper discusses the symposium and the literature that supported it.

There are many ideas, textbooks and software designed to help students understand statistical thinking. The following papers discuss what good courses in statistics should contain. Although they were published in 1999 and 2002, the basic ideas are still true today.

- First Courses in Statistical Science: The Status of Education Reform Efforts by Joan Garfield,
*et al*(2002) - J. Higgins. Nonmathematical Statistics: A New Direction for the Undergraduate Discipline. The American Statistician, Vol. 53, No. 1, Feb. 1999.

### 3. Statistics Majors and Minors

The ASA is currently updating its curriculum guidelines for undergraduate programs in statistical science (http://www.amstat.org/education/curriculumguidelines.cfm), which came out of the ASA's Undergraduate Statistics Education Initiative (USEI, 2000). The updated guidelines will remain true to the original guidelines, while allowing for an increased emphasis in topics such as "big data" and statistical software.

#### Statistics Majors

Undergraduate programs in statistics should prepare students to work with data through an emphasis on both theory and practical experience. Students need the analytical skills of a data scientist as well as necessary mathematical skills. Below are brief summaries of the current (winter 2014) guidelines for two possible curriculum designs.

**BA in statistics**

The **ASA Guidelines** (http://www.amstat.org/education/pdfs/BA-curriculum.pdf) provide a summary:

A. Mathematics: Calculus I, II, III; linear algebra; probability

B. Core Statistics

• Data production (experimental design, sampling, observational studies)

• Applied modeling (regression, ANOVA, methods for categorical data)

• Inference (least squares and maximum likelihood estimation, tests and intervals)

• Emphasize real data, statistical computing, synthesis, and communication

C. Substantive Area: minor or concentration in an area of application

**BS in statistics**

The paper by Bryce, et al, (http://www.amstat.org/education/pdfs/BS-curriculum.pdf) describes some of the history of the recommendations, and the core skills needed. The current curriculum recommendations appear in section 4.2 and guidance on electives appears in section 4.3.

#### Statistics Minors

The **ASA Curriculum Guidelines** suggest that a minor consists of 2 core courses (for example, an introductory statistics course and a modeling or applied regression course), and 3 to 5 elective courses.

http://www.amstat.org/education/resourcesforundergradminors.cfm

The paper by Ann Cannon, *et al*.

(http://www.amstat.org/publications/jse/v10n2/cannon.html) expands on the general guidelines and offers some answers to questions that might arise about a particular curriculum design or revision.

### 4. Supporting and Evaluating Statisticians within Mathematics Departments

It may be useful for candidates under review and department chairs to consider portions of the Mathematical Association of America (MAA) Guidelines for programs and Departments (http://www.maa.org/programs/faculty-and-departments/curriculum-department-guidelines-recommendations/guidelines-for-the-profession) and the American Statistical Association (ASA) Response to these guidelines (http://www.amstat.org/policy/pdfs/ASAEndorsementMAA2000Guidelines.pdf). Below are some key points made in this endorsement:

- Ideally, mathematical sciences departments in which statistics courses are taught should hire faculty with graduate degrees in statistics.
- Once a mathematical sciences department has successfully hired statistics faculty, it should provide sufficient resources and mentoring to enable them to succeed in their teaching and professional development. While travel funds are important for all new faculty members, they can be especially important for statisticians who are housed in a department of non-statisticians. These faculty members have a particular need for travel to conferences and workshops in order to meet with collaborators and gain new ideas about the teaching of statistics.
- Mathematical sciences departments should also recognize the value of statistical consulting as a legitimate and important form of scholarship and professional development.
- If a statistician is expected to provide consulting services to colleagues and students throughout the institution…then the institution should make reassigned/released time available for that purpose.
- If the department has only one or two statistics faculty members, it should seek outside persons to serve as advisors for the department and mentors for these isolated faculty members early in their careers.
- When a department with only one statistician is evaluating the person's teaching, the department should seek input from statisticians at nearby institutions or from the ASA. Since the teaching of statistics differs from that of mathematics in several ways, this input can help the department to assess whether the statistician's teaching is consistent with expectations and recommendations in the field.
- The ASA strongly supports the position that mathematics and statistics are separate disciplines and that statistics courses should be taught by those trained in the subject. "In cases where a department offers a course or courses in a particular discipline, but does not have a faculty member with expertise in that discipline, the department should take special care to consult the curricular guidelines of the relevant professional society in that discipline." (MAA guidelines section D.1.g)

We encourage mathematics departments not to be overly prescriptive in stating what is adequate in terms of professional involvement for a statistician. While statisticians should be able to provide evidence that they are working in their field(s) as engaged scholars, this work may look different than research in mathematics. It is important to recognize that the interdisciplinary nature of statistics encourages a wide range of scholarly activities. For example, scholarly engagement may emphasize integration, organization, and synthesis, such as the creation of software, consulting within multiple disciplines, publishing in journals outside of their field, leading workshops, presenting at conferences, or pursuing research grants. It is best to provide clear expectations for scholarship in writing to any statistician that is hired within a mathematics or mathematical sciences department. Below is a limited set of perspectives on hiring statisticians

- http://www.amherst.edu/~nhorton/Everson-liberal.pdf
- http://www.ams.org/profession/employment-services/eims/eims-charlwood-oct05.pdf
- Kuiper, S.; Legler, J.; and Morgan, C. (2005). "Choosing a Career as a Statistician in a Liberal Arts College."
*AmStat News*, V339, 22-24