UNIVERSITY STUDY GROUP

“Review of Statistical Education at Texas Tech University”

Final Report, September 2005

Executive Summary

A committee comprised of representatives from every College was convened by Dean John Borrelli to study statistics education (at both undergraduate and graduate levels) at Texas Tech University. The committee compiled an extensive database of statistics courses offered at TTU, and summarized the resulting information to provide descriptive data on enrollment, presented by academic unit as well as by college. Most of the statistics education at the undergraduate level is provided by courses offered by the Department of Mathematics and Statistics; in contrast, most of the statistics coursework at the graduate level is provided by departments other than Mathematics and Statistics. A survey of major topics presented in these courses was developed. Resulting information provides the basis for recognizing areas of statistical expertise on campus as well as a justification for the proposal of an interdisciplinary minor in statistics at the doctoral level. The database also reveals possible subjects/topics in statistics that are currently not offered, and thus provides an opportunity for interested faculty to develop new courses that will enhance the quality of statistics education at Texas Tech University. It is recognized that the teaching of statistics is most effective when the subject is approached through a combination of sound theoretical background and “hands-on”, applications-oriented examples. It is also recognized that whereas many statistical educators feel that statistics is best taught by statisticians, others express equally strong opinions that students learn statistics best when it is taught by qualified instruction in the subject-matter specific to the student. In either case, it is recognized that SACS guidelines as well as TTU Operating Policies mandate that individual departments and colleges are responsible for ensuring that instructors are properly qualified to teach statistics at Texas Tech University.

Final committee recommendations may be found on page 16.

Committee Members:

Peter Westfall, chair, Jerry S. Rawls College of Business AdministrationRuth Maki, College of Arts and SciencesHossein Mansouri, College of Arts and SciencesArturo Olivarez, College of EducationWilliam Lan, College of EducationJohn Kobza, College of EngineeringAlan Reifman, College of Human SciencesDavid Wester, College of Agricultural Sciences and Natural ResourcesJohn Borrelli, Dean, Graduate School

Original Charge for Committee to Review Teaching of Statistics From John Borrelli, Dean of Graduate School, May, 2004

  The Provost has been asked to report at a future Board of Regents meeting steps that have been taken to review redundant or low productivity programs and courses.  At the same time, the Graduate Council has seen several new courses in statistics where there appears to be significant overlap with existing courses.   I asked the Provost to appoint a committee to review how statistics is being taught at Texas Tech and to determine if we could minimize the overlap of statistic courses.  He said in effect, great idea, please do it.  The teaching of statistics and meeting the needs of all stakeholders is not an easy or simple task.  If I may make an analogy, it is like trying to improve the flow of goods and services to the City of Chicago.  The current system some how works although some planners believe they can improve on the system.  Trying to improve on a system that has evolved over decades is a daunting task.  Nevertheless, this is what we are asking you to do.  We want you to review our current academic courses and programs that supply statistical education to our students and determine if we can improve on the quality of their statistical education while reducing the costs of providing statistical educational to our students.  Goals Provide our students (undergraduate and graduate) state-of-the-art statistical education up to the level the students need to accomplish their needed level of statistical literacy.  For example, some students may require just simple means, standard deviations, and simple correlations while others may need to understand how to use ANOVA and multi-regression analyses.   Have our students gain experience in applying the correct statistics to problems in their specific area of study.  For example, civil engineers should be able to select the correct distribution to represent flood frequencies and know the difference between a two-parameter and a three-parameter distribution.  An agronomist should be able to setup a factorial experiment that compares several different treatments and be able to evaluate the interactions.  It appears the numerous courses in statistics have been developed to provide the type of statistics needed and its application to problems in a particular field of study.  Everyone appears to be using the same statistical programs such as SAS so there must be some underlying common set of statistical theory.  The real differences in many of the courses are the applications.   Products from Committee Product #1: Develop an inventory of statistical courses which details content, prerequisites, the instructors, and the intended audience. Product #2: Recommend ways to teach state-of-the-art statistical procedures to both undergraduate and graduate students. Product #3: Recommend ways to provide content specific applications to both undergraduates and graduate students. Please note that continuing to do the same thing as we currently doing in teaching statistics in all parts of campus may be an acceptable recommendation if determined by the proposed study. 

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(Dean Borrelli charge to committee, continued)

Cautions There have been many changes in programs, attitudes, and the ability to deliver course materials that have occurred in the past 20 years.  I am sure you will find reasons why courses were developed based on conditions that no longer exist.  You will also find resistance to change and territorial instincts in play.  Do not allow these memories of past conditions to prevent you from finding optimum solutions and making academically sound recommendations.  Considerations Use Institutional Research to help gather data on courses, class sizes, when courses were taught, etc.  They may not be able to provide all the information desired, but they can be very helpful in gathering data. Upon completion of the inventory of current statistical offerings, please share this information with the Provost and all Deans.  This information should provide a good picture of the number of courses and SCHs earned for the university as a whole in the area of statistics.

======= End of Dean Borrelli Charge to Committee =======

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Committee Findings

Committee’s Interpretation of Its Charge

The committee will review statistics courses at Texas Tech and make recommendations aimed at improving the quality of statistics education, and enhancing the research mission of Texas Tech University. Through its integrative processes, the recommendations of this committee will lead to:

A more quantitatively and scientifically literate student body and faculty, Improved placement of students, and Improved research productivity, both in terms of journals and funded projects, for

students and faculty.

Committee’s Definition of “Statistics Course”

Many courses are taught at Texas Tech that use statistics in one way or another. Thus, a first task of the committee was to define what is meant be a “Statistics Course.” The committee adopted the following definition:

A “statistics course” is any course during which more than 50% of instructional time is spent covering probability, statistics, or statistical software (SAS, SPSS, Amos, Lisrel, Minitab, SPLus, R, Stata, Limdep, Eviews, etc.) in a “generic” way (that is, in a way that requires no discipline-specific prerequisite).

Committee Results Web Page

This report, further details, databases, and hyperlinks useful for improvement and assessment of statistics education at Texas Tech University, are available on the committee web site,

http://westfall.ba.ttu.edu/statcourses/statcourses.htmWe emphasize that the information included in this database was gathered during the period from calendar years 2003 through 2004, and represents the best information available at the time of compilation.

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Committee Actions on Product Deliverables – Product #1

Product #1:

Develop an inventory of statistical courses which details content, prerequisites, instructors, and intended audience.

Action on Product #1:

With student support and support of TTU Institutional Research, the committee compiled a database of “statistics” courses (as defined above) taught at Texas Tech, undergraduate as well as graduate. The database contains information on: College, Department, Course Number and Name, Enrollments, Prerequisites, link to recent syllabus (when available), Topical Coverage, (as judged from the syllabus and/or TTU catalog description) and Software Usage (as indicated on the syllabus and/or TTU catalog description).

Enrollment Reports

An overview of statistics courses taught by various campus units and enrollment is shown in Figures 1 through 4. The following observations are noteworthy:

1. A total of 100 statistics courses are offered at Texas Tech University. These courses enroll an average of 6014 undergraduate students and 1487 graduate students each academic year. A total of 144 faculty (some teach multiple sections) are involved in statistical instruction on campus.

2. It is noteworthy that the percentage of courses in the Rawls College of Business is relatively lower than the percentage of students (14% vs. 24%), indicating larger class sizes and fewer classes.

3. Comparing the undergraduate- and graduate-level courses, the majority of undergraduate statistics education occurs in the Department of Mathematics and Statistics (67% percent of the class offerings and 71% of the total enrollments), but the majority of graduate statistics education occurs elsewhere (84% of the course offerings and 88% of the students are outside of the Department of Mathematics and Statistics).

Specific data and breakdowns are given in Appendices II and III.

Appendix II summarizes total enrollments by college, broken down by graduate and undergraduate, in calendar years 2003-2004. Since some courses are offered only once every other year, it was essential to include a two-year span for reporting purposes.

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Figure 1. Percent of total graduate statistics courses taught by various academic units, 2003-2004 calendar years.

Figure 2. Percent of total graduate students in statistics courses taught by various academic units, 2003-2004 calendar years.

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Figure 3. Percent of total undergraduate statistics courses taught by various academic units, 2003-2004 calendar years.

Figure 4. Percent of total undergraduate students in statistics courses taught by various academic units, 2003-2004 calendar years.

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Topical Coverage

The committee attempted to categorize topical coverage in statistics courses using information available in the course catalogue, the recent syllabi, and in some cases, by direct communication with the current instructors. We recognize that many of these topics can not be taught in isolation: e.g., “hypothesis testing” (HT) is probably covered in courses that teach “analysis of variance/covariance” (AVC), and so topical overlap is to be expected. The figure was not intended to convey this aspect of “topical coverage”, but rather to highlight topics, as found in course syllabi and course catalogue descriptions, to illustrate the frequency of their coverage.

Figure 5. Topical coverage of graduate level courses based on % of total number of courses2003-2004. LRA=Linear Regression, AVC=ANOVA/ANCOVA, HT=Hypothesis

testing, PD=Probability Distributions, PT=Probability Theory, NS=Nonparametric Statistics, BC=Basic Concepts, AC=Analysis of Correlation, MA=Multivariate Analysis SDC=Sampling/Data Collection, TSP=Time Series/Stochastic Processes, GLNM=General Linear/Nonlinear Model, DEH=Design of Experiments/Human Subjects, SDA=Survey Design/Data Analysis, MC=Multiple Comparisons, EDA= Exploratory Data Analysis, NRA=Nonlinear Regression Analysis, CDA=Categorical Data Analysis, DEI=Design of Experiments/Industrial, SEM=Structural Equations Models, DEBC= Design of Experiments/Biological or Clinical, QC=Quality Control.

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Note: The topics covered in less 5% of courses are not shown in this graph. See Table 4-1 in appendix for more detail.

Figure 6. Topical coverage of undergraduate level courses based on % of total number of courses. 2003-2004. PD=Probability Distributions, HT=Hypothesis Testing, LRA=Linear Regression Analysis, PT=Probability Theory, BC=Basic Concepts, SDC=Sampling/ Data Collection, AVC=ANOVA/ANCOVA, SDA=Survey Design/Analysis, AC= Analysis of Correlation, DEH=Design of Experiments/Human Subjects, CDA= Categorical Data Analysis, QC=Quality Control, EDA=Exploratory Data Analysis, NRA=Nonlinear Regression Analysis, DEI=Design of Experiments/Industrial, MA= Multivariate Analysis, NS=Nonparametric Statistics.

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Note: 1. The topics covered in less 5% of courses are not shown in this graph.

Figure 7. Usage of software package based on percentage of total number of statistical courses2003-2004

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Committee Actions on Product Deliverables – Products #2, 3

Product #2: Recommend ways to teach state-of-the-art statistical procedures to both undergraduate and graduate students.

Product #3: Recommend ways to provide content specific applications to both undergraduates and graduate students.

Actions on Products 2 and 3:The discipline of Statistics is, by its nature, integrative, and it is difficult to divorce these products completely. Still, Product #2 seems to emphasize statistics teaching of a more “theoretical” nature, and Product #3 seems to emphasize teaching of statistics of a more “applied” nature.

The committee’s response to these to deliverables was (a) to gather data and explore the issue of the effectiveness of teaching statistics in different departments and by faculty with greater or lesser degrees of training in statistical theory and methods, and by faculty with greater or lesser degrees of application knowledge, and (b) to recommend methods for improvement of statistical education in general, not distinguishing between Products 2 and 3, since, by the nature of the discipline of Statistics, the products cannot be entirely separated in any case.

Is statistics more effective when taught within disciplines or when taught in statistics departments?

As seen in Figures 1 and 2, much teaching of statistics occurs outside the department of Mathematics and Statistics, especially at the graduate level. Because one of the goals of the committee was to consider ways to improve the teaching of statistics, and because many on the committee are actively involved in teaching statistics classes, the committee researched this question thoroughly in the academic literature and on the internet. The following are the findings of the committee:

Some individuals hold personal opinions that statistics is more effective when taught within disciplines, because the subject is more relevant and accessible to students. Others hold personal opinions that when taught within disciplines, statistics tends to be “watered down” to such an extent that it may provide a less effective statistical education. However, in the review of the literature, there was no scientific data to support either opinion. In one conference devoted to the subject of teaching statistics called “United States Conference on Teaching Statistics” (http://www.causeweb.org/uscots/), the assumption generally seems to be that statisticians are doing the teaching, while in the conference “Making Statistics More Effective in Schools of Business” (http://www.msmesb.org/), it is generally assumed that business professors with statistical training are doing the teaching. There seem to be no data or studies on a comparative assessment of the educational effectiveness of these different avenues of instruction.

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The review of the literature indicated broad consensus that applications and “hands-on” data analysis is effective, regardless of whether the instruction is within the discipline of statistics, or within the disciplines that use statistics.

Recommendation of Committee Concerning Where Statistics is Taught, Who Teaches Statistics, and How Statistics is Taught

Wherever, whoever, and however statistics are taught, guiding principles of the Southern Association of Colleges and Schools (SACS), TTU’s main accrediting agency, as well as TTU Operating Policies (OPs) should be followed. Relevant requirements from the most recent SACS Principles of Accreditation: Foundations for Quality Enhancement (http://www.sacscoc.org/pdf/PrinciplesOfAccreditation.PDF) are the following:

SACS Comprehensive Standards 3.3.1 and 3.4.1 are concerned with assessment and quality improvement:

SACS Comprehensive Standard 3.3.1: The institution identifies expected outcomes for its educational programs and its administrative and educational support services; assesses whether it achieves these outcomes; and provides evidence of improvement based on analysis of those results.

SACS Comprehensive Standard 3.4.1: The institution demonstrates that each educational program for which academic credit is awarded (a) is approved by the faculty and the administration, and (b) establishes and evaluates program and learning outcomes.

Committee Discussion of SACS Comprehensive Standards 3.3.1 and 3.4.1:

On the committee web page http://westfall.ba.ttu.edu/statcourses/statcourses.htm, numerous teaching resources are made available under “Statistics Links of Interest.” One committee member (Alan Reifman) attended a conference on teaching statistics in May 2005 (The United States Conference on Teaching Statistics, http://www.causeweb.org/uscots/), materials from which on statistics assessment and teaching strategies are available on the conference web site and on our committee website.

The committee also recommends a recent series of articles on training of statistics teachers appears in The American Statistician Vol. 59(1), February, 2005, 1-18; titles are “Preparing Graduate Students to Teach Statistics”, “A Course on Teaching Statistics at the University Level,” “Training Statistics Teachers at Iowa State University,” “Training Graduate Students at Penn State University in Teaching Statistics,” and TA Training at Virginia Tech: A Stepwise Progression.”

The committee also recommends “Wildlife Society Bulletin” 2001, Vol. 29, which published a special section entitled “Biometrics in Undergraduate Education”, with

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articles such as “Importance of biometrics education to natural resource professionals”; “Integrating mathematics and statistics into undergraduate wildlife programs”, “Infusing quantification into a fisheries and wildlife undergraduate curriculum”, “Rigor in wildlife education: where the rubber hits the road”, “Quantification training of wildlife graduate students”, “Wildlife biometrics training at the Univ. of Georgia: adding quantitative emphasis to a wildlife management program”, and “Statistics for wildlifers: how much and what kind?”

The American Psychological Association created a task force on statistical inference which published an article describing recommendations for statistical methodology. The committee also recommends this article for statistics instructors in all fields; the reference is Wilkinson, Leland (1999), “Statistical methods in psychology journals: Guidelines and explanations,” American Psychologist, Vol 54(8), Aug 1999. pp. 594-604.

SACS Comprehensive Standards 3.6.1 is concerned with graduate courses:

SACS Comprehensive Standard 3.6.1: The institution’s post-baccalaureate professional degree programs, and its master’s and doctoral degree programs, are progressively more advanced in academic content than undergraduate programs.

Committee Discussion of SACS Comprehensive Standards 3.6.1:

Whereas the committee did not make a determination of whether all the graduate courses are more advanced than the undergraduate courses, there is perhaps a concern in that a number of graduate courses seem “elementary” by their course catalog descriptions and/or syllabi. The committee recommends that individual departments ensure that their statistics courses meet SACS standard 3.6.1, and recommends that undergraduate leveling courses in basic statistics might be recommended in some cases for graduate students who have not had undergraduate statistics; the course database compiled by the committee (http://westfall.ba.ttu.edu/statcourses/ALLStatCourses_COVERAGE_updated2.xls, on the committee web page http://westfall.ba.ttu.edu/statcourses/statcourses.htm) may be helpful for advisors in this regard.

SACS Comprehensive Standard 3.7.1 is concerned with teacher qualifications:

SACS Comprehensive Standard 3.7.1: The institution employs competent faculty members qualified to accomplish the mission and goals of the institution. When determining acceptable qualifications of its faculty, an institution gives primary consideration to the highest earned degree in the discipline in accordance with the guidelines listed below. The institution also considers competence, effectiveness, and capacity, including, as appropriate, undergraduate and graduate degrees, related work experiences in the field, professional licensure and certifications, honors and awards, continuous documented excellence in teaching, or other demonstrated competencies and achievements that contribute to effective teaching and student learning

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outcomes. For all cases, the institution is responsible for justifying and documenting the qualifications of its faculty.

Credential Guidelines:a. Faculty teaching general education courses at the undergraduate level: doctor’s or master’s degree in the teaching discipline or master’s degree with a concentration in the teaching discipline (a minimum of 18 graduate semester hours in the teaching discipline).b. Faculty teaching associate degree courses designed for transfer to a baccalaureate degree: doctor’s or master’s degree in the teaching discipline or master’s degree with a concentration in the teaching discipline (a minimum of 18 graduate semester hours in the teaching discipline).c. Faculty teaching associate degree courses not designed for transfer to the baccalaureate degree: bachelor’s degree in the teaching discipline, or associate’s degree and demonstrated competencies in the teaching discipline.d. Faculty teaching baccalaureate courses: doctor’s or master’s degree in the teaching discipline or master’s degree with a concentration in the teaching discipline (minimum of 18 graduate semester hours in the teaching discipline). At least 25 percent of the discipline course hours in each undergraduate major are taught by faculty members holding the terminal degree—usually the earned doctorate—in the discipline.e. Faculty teaching graduate and post-baccalaureate course work: earned doctorate/ terminal degree in the teaching discipline or a related discipline.f. Graduate teaching assistants: master’s in the teaching discipline or 18 graduate semester hours in the teaching discipline, direct supervision by a faculty member experienced in the teaching discipline, regular in-service training, and planned and periodic evaluations.

In addition, TTU OP32.02 is concerned with Certification of Faculty Qualifications.

TTU OP 32.02(2.a.) Baccalaureate Faculty – Section 3: Comprehensive Standards: Programs: Faculty: 3.7.1.d of the Principles

All full-time and part-time faculty members teaching courses leading toward the baccalaureate degree, other than physical education activity courses, must have completed at least 18 graduate semester hours in the teaching discipline and hold at least a master's degree. Outstanding professional experience and demonstrated contributions to the teaching discipline may be presented on an exceptional basis in lieu of formal academic preparation. Such individual cases must be justified as herein provided.

Appropriate credentials for teaching interdisciplinary courses may vary. The academic and professional preparation of faculty members teaching in such courses or programs must be documented and justified, as provided herein, on a case-by-case basis

TTU OP 32.02(2.b.) Graduate Faculty – Section 3: Comprehensive Standards: Programs: Faculty: 3.7.1.e of the Principles

Each faculty member teaching courses at the master's and specialist degree level must hold the terminal degree, usually the earned doctorate, in the teaching discipline or a related discipline. In some instances, the master's degree in the discipline may be considered the terminal degree,

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while in others, a master's degree in the discipline coupled with a doctorate in a related discipline may be appropriate. In the latter cases, the master's degree, or master's degree coupled with a related earned doctorate, must be justified as the terminal degree as provided herein.

All faculty members teaching at the doctoral level must hold the earned doctorate in the teaching discipline or a related discipline. However, in unusual cases, at the request of the department offering the course and with the prior approval of both the appropriate academic dean and the graduate dean, individuals with special abilities may teach doctoral courses --these generally would be people who have demonstrated exceptional scholarly or creative activity or substantial professional experience.

TTU OP 32.02(2.c.) Graduate Teaching Assistants – Section 3: Comprehensive Standards: Programs: Faculty: 3.7.1.f of the Principles

Graduate teaching assistants who have primary responsibility for teaching a course for credit and/or assigning grades must have earned at least 18 graduate hours in the teaching discipline. Those not meeting the requirements for baccalaureate faculty described in section 2.a must also be under the direct supervision of a faculty member experienced in the teaching discipline, must receive regular in-service training, and must be evaluated regularly. The requirements above do not apply to graduate teaching assistants engaged in assignments such as teaching physical education activities, assisting in laboratory sessions, attending or helping prepare lectures, paper grading, keeping class records, and conducting discussion groups. Graduate teaching assistants for whom English is a second language may be appointed only when a test of spoken English or other reliable evidence demonstrates proficiency in oral and written communication. Satisfactory completion of the summer workshop, described more fully in OP 64.03, is required for all international graduate teaching assistants.

Committee Discussion of SACS Comprehensive Standards 3.7.1 and TTU OP32.02:

Individual departments and colleges in which statistics courses are taught are responsible for ensuring that those who teach statistics courses meet the qualifications above that are set forth in SACS Comprehensive Standard 3.7.1 and TTU OP 32.02.

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Final Committee Recommendations

1. It is expected that the objectives of the Dean of the Graduate School and the Graduate Council concerning statistics teaching at Texas Tech can be met through open and broad communication of the outputs of this committee. To these ends,

a. this report and the corresponding web page http://westfall.ba.ttu.edu/statcourses/statcourses.htm should be made available to all faculty through Tech Announce,

b. it should be sent to all department chairs and deans where statistics courses are taught, and

c. all graduate advisors should be sent an executive summary along with the web page http://westfall.ba.ttu.edu/statcourses/statcourses.htm, so that they may advise their students concerning statistics courses that are available campus-wide.

2. In the future, attempts should be made periodically to update the content on the committee webpage (http://westfall.ba.ttu.edu/statcourses/statcourses.htm), so that it will remain useful.

3. In the process of developing materials for this report, it became clear to the committee and to the Dean of the Graduate School that we have the ability to offer a TTU Interdisciplinary program in Statistics that will enable students to attain a “minor” in statistics that can be satisfied by taking courses, both theoretical and applied, in a variety of departments and academic units. Therefore, to raise the overall level of statistical expertise at Texas Tech, for faculty, researchers, and students alike, the committee recommends that TTU institute the Interdisciplinary Statistical Science Ph.D. minor/graduate certificate program. Details are spelled out in Appendix I.

4. The information compiled in the database highlight not only the strengths of the statistics education provided at Texas Tech University, but also reveal weaknesses in areas of topical coverage, particularly with respect to aspects of the field of statistics that extend beyond the “traditional” training in, for example, analysis of variance and linear models, linear regression, experimental designs, and sampling/survey statistics. No less than other academic disciplines, the field of statistics is dynamic and progressive, and it is incumbent upon the educators of statistics at Texas Tech University that we provide our students with the best of statistical training—and this includes a strong foundation in traditional statistics as well as an exposure to the newest techniques available. In this regard, the report will reveal to faculty on campus areas of statistical training that can be explored more fully through the development of new courses for our students. It is therefore strongly advised that any faculty member who wishes to develop a new statistic course at TTU consult with this report first.

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Appendix I: Interdisciplinary Statistical Science A Proposed Ph.D. Minor Program

Interdisciplinary Statistical Science is offered as an interdisciplinary minor for those who wish to improve their statistical skills, whether for research, teaching, or employment opportunities. Statistics is used extensively in most, if not all, areas of research, including biological, business, engineering, medical and social sciences. Researchers use statistical theory and methods to design studies and data collection instruments, to select appropriate analytic tools, and to interpret results of the data analysis. In the business world, statistics are used for administration and management of business processes, to make forecasts and to plan, to make decisions, and to optimize resource allocation.

What is statistics? Statistics is the science of collecting, interpreting, learning from, and making decisions from data. The discipline is interdisciplinary, and appears in various business and academic disciplines under slightly different names. These include “Biostatistics,” “Business Analytics,” “Data Mining,” “Econometrics,” “Design of Experiments,” “Forecasting,” “Psychometrics,” and “Research Methods.”

The goal of the Interdisciplinary Statistical Science program is to teach advanced skills needed to function as a statistical specialist in one’s chosen discipline. Statistical specialists should have (i) theoretical foundational skills, (ii) computer and statistical software skills, and (iii) a variety of applications skills.

The Ph.D. minor in Interdisciplinary Statistical Science consists of 18 graduate hours and additional undergraduate hours as needed. At most 9 graduate hours may be taken from a single department or area. At least two courses will be taken from the Department of Mathematics and Statistics.

Foundational Skills: Mathematical Statistics. At least two courses from the following list will satisfy this goal, at least one of which must be at the graduate level. These courses should be taken first. (In disciplines with typically less mathematics knowledge, it might be possible to make special arrangements on a case by case basis, as approved by the committee.)MATH 3342 Mathematical Statistics for Engineers and ScientistsMATH 4342 Mathematical Statistics IMATH 4343 Mathematical Statistics IISTAT 5328 Intermediate Mathematical Statistics ISTAT 5329 Intermediate Mathematical Statistics IIISQS 5347 Advanced Statistical Methods

Computer Skills: Hands-on experience with statistical software packages exposure or, optionally, relational databases or other computer-intensive coursework. Two courses from the database of statistics courses (http://westfall.ba.ttu.edu/statcourses/ALLStatCourses_COVERAGE_updated2.xls) that give hands-on experience with different statistical software packages are required. A non-statistics course that gives hands-on experience with relational databases, or other non-statistical computer-intensive hands-on course may be substituted for one of these courses.

Applications Skills: Regression, Multivariate Analysis, ANOVA, SEM, etc, at student’s discretion. Courses may be selected from the list in http://westfall.ba.ttu.edu/statcourses/ALLStatCourses_COVERAGE_updated2.xls.

Approval of Programs of Study: A coordinating committee shall be chosen by, and shall report to the Dean of the Graduate School. Programs will be initiated by students, and will be eligible for certificate/minor only if approved by the committee.

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Appendix II: Tables

Table 1-1. Enrollment by course, 2003-2004, College of Arts and Sciences.

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Table 1-2. Enrollment by course, 2003-2004, College of Ag Sciences and Natural Resources.

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Table 1-3. Enrollment by course, 2003-2004, Rawls College of Business Administration.

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Table 1-4. Enrollment by course, 2003-2004, College of Education.

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Table 1-5. Enrollment by course, 2003-2004, College of Engineering.

Table 1-6. Enrollment by course, 2003-2004, College of Human Sciences.

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Table 2-1. Enrollment by department, 2003-2004, College of Arts and Sciences.

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Table 2-2. Enrollment by department, 2003-2004, College of Ag Sci. & Nat. Res.

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Table 2-3. Enrollment by department, 2003-2004, Rawls College of Business Administration.

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Table 2-4. Enrollment by department, 2003-2004, College of Education.

Table 2-5. Enrollment by department, 2003-2004, College of Engineering.

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Table 2-6. Enrollment by department, 2003-2004, College of Human Sciences.

Table 3-1. Enrollment by college, 2003-2004, graduate.

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Table 3-2. Enrollment by college, 2003-2004, undergraduate.

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Table 4-1. Topical coverage, 2003-2004. Raw=count of courses. % =count/(total number of graduate statistics courses offered).

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Table 4-2. Topical coverage, 2003-2004. Raw=count of courses. % =count/(total number of undergraduate statistics courses offered).

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Table 5-1. Software usage, 2003-2004. Raw=count of courses. % =count/(total number of graduate statistics courses offered).

Table 5-2. Software usage, 2003-2004. Raw=count of courses. % =count/(total number of undergraduate statistics courses offered).

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