ARCOTS

List of Participants

PROGRAM

Pictures

Invited Speakers

Abstracts of Short Talks & Posters

Appalachian Regional Conference On Teaching Statistics

ARCOTS

March 29th, 2003
Forum - Culp Center
East Tennessee State University
Johnson City, Tennessee

Titles of Invited Talks

Ready, Tech, Go : If technology has revolutionized the teaching of statistics, why are we still teaching the same old course?

Incorporating Technology into Introductory Statistics Classes: Active Learning Java Applets for Demonstrating Key Concepts

Learning Statistics: An Experiment Comparing Online and In class instruction

INVITED SPEAKERS:

Richard D. De Veaux - Professor of Statistics in the Department of Mathematics and Statistics at Williams College, ASA Fellow, with extensive research in Neural Networks, Data Mining and applied statistics. Has received several teaching and research awards. Author of a new Introductory Statistics book and forthcoming books on Data Mining and Experimental Design. In his spare time he leads a doo-wop quartet (the "Diminished Faculty"), bicycles and is the father of four children.

Christine Anderson-Cook - Associate Professor in the Department of Statistics at Virginia Tech. Co-Developer of Statistical Java, a free web-based package to help demonstrate statistical concepts for introductory statistics classes. Associate book review editor for the Journal of the American Statistical Association and The AmericanStatistician. Research areas include statistics education, response surface methodology,graphical methods, design of experiments, directional data, and applications of statistics in engineering, crop and soil sciences, pharmacology, geology and food sciences.

Jessica Utts - Professor in the Department of Statistics at UC Davis, ASA and IMS Fellow. Member (1997-2002) and Chair (1999-2002) of the Advanced Placement Statistics Development Committee. Numerous publications in the areas of regression, robustness, applied statistics and the use of statistics in research in psychology and parapsychology. Extensive consulting experience and numerous TV interviews including CNN, ABC Nightline, Larry King Live. Recipient of teaching awards and author of the books: Seeing Through Statistics and Mind on Statistics (with Robert
Heckard). Editor-in-chief of CyberStats."

Program

8:30- 9:00 Arrival / Registration/ Coffee

9:00-9:05 Welcome- Anant Godbole, Chair, Math Department ETSU

Session 1: Teaching Philosophy, Methods, and Strategies

9:05-10:00 Ready, Tech, Go : If technology has revolutionized the teaching of statistics, why are we still teaching the same old course?
Richard D. De Veaux, Williams College, Williamstown, Massachusetts

Session Chair: Janice Huang (ETSU)

10:05 -10:20 Strategies for teaching confidence intervals
Scott Preston, State University of New York, Oswego, New York

10:25-10:40 FreeCell, Students, and Statistics
Paul Baker, Catawba College, Salisbury, North Carolina

10:45-11:00 Sampling Experiments for Teaching Statistics
Michael J Symons* and Dana Quade, University of North Carolina, Chapel Hill- North Carolina. * presenting author

11:05-11:20 Our Experience in Group Projects
Hasan Hamdan and Arlene R. Casiple, James Madison University, Harrisonburg, Virginia
(10 minute break)

Session 2 : Use of Technology

Session Chair: Lyndell M. Kerley (ETSU)

11:30-12:15 Incorporating Technology into Introductory Statistics Classes: Active Learning Java Applets for Demonstrating Key Concepts
Christine Anderson-Cook, Virginia Tech, Blacksburg, Virginia

12:15 – 1:10 LUNCH BREAK
(Dining Room # 2)

1:10-1:25 A statistics application software in Java
Kevin R. Doheny, Dalton State College, Dalton, Georgia

1:30 -1:45 The Cave Project – Teaching introductory statistics in an 'active-learning / computer-enhanced' environment
Jeff Knisley, Robert Price Jr., and Edith Seier, East Tennessee State University, Johnson City, Tennessee

1:50-2:10 Using a NSF- CCLI Grant to Improve Instruction in Introductory Statistics
Cathy Witlock, Dot Sulock, and Steve Patch, University of North Carolina, Asheville, North Carolina
(10 minute break)

Session 3: On-Line Instruction

Session Chair: Nancy M.Pfenning (University of Pittsburgh)

2:20 -3:15 Learning Statistics: An Experiment Comparing Online and In class instruction
Jessica Utts, University of California, Davis, California

3:20-3:35 Experiences from an Online Introductory Level Biostatistics Course - What Does and Does Not Work
Gail Tudor, University of North Carolina, Chapel Hill, North Carolina.

3:40-3:55 Comparison of Streaming Media Technology for the classroom
Michael Allen, Tennessee Technological University, Cookeville, Tennessee

3:55-4:20 Poster Session (Dining Room # 1) - Refreshments will be served. Coordinator: Susan Hosler (ETSU)
Developing an introductory statistics course with R
Motoya Machida, Tennessee Technological University, Cookeville, Tennessee

myJavaStat: an Environment for Teaching Statistics
E. James Harner - West Virginia University- Morgantown- West Virginia

Sampling Simulators for Use in the Introductory Statistics Classroom.
Mary Ella Poteat and Malissa Trent, Northeast State, Technical Community College, Blountville, Tennessee

4:20-5:00 Panel discussion

Panelists: Christine Anderson-Cook, Richard DeVeaux, Jessica Utts
Moderator: Edith Seier

Participiants
in the conference

1   Allen, Michael - Tennessee Technological University
2   Anderson-Cook, Christine - Virginia Tech
3   Baker, Paul - Catawba College, SC
4   Bangurah, Franklin   - Walters State C.C., TN
5   Bay, Jeff   - Maryville College, TN
6   Bowman, Troy    -Walters State C.C., TN
7   Butler, Murray - ETSU
8   Byington, Randy - ETSU
9   Campell, Ted   - Northeast State Technical C.C., TN
10   Cannon, Newt   -W.H.Freeman
11   Canon, Dwala - Duxbury
12   Casiple, Arlene R. - James Madison University, VA
13   Culbert, Sam - Science Hill High School, TN
14   Dabney, Dawn R. - Northeast State Technical C.C.,TN
15   Daugherty, Scoot   - Tusculum College, TN
16   DeVeaux, Richard -   Williams College, MA
17   Doheny, Kevin R. - Dalton State College, GA
18   Edwards, Billy - Univ. of Tennessee at Chattanooga
19   Ellis, Robert W. - University of Tennessee
20   Gillespi, Wayne - ETSU
21   Godbole, Anant - ETSU
22   Gregory, Julianna - Walters State C.C.,TN
23   Griffith, Shane   - Lee University,TN
24   Hamdan, Hasan - James Madison University, VA
25   Harner, Jim - University of West Virginia
26   Helfgott, Michel   - SUNY Oswego,NY
27   Hespen Golek, Jennifer - Univ. of Tennesee
28   Higgins, Terry    University of Tennesse
29   Higgins, Jennifer - University of Tennessee
30   Hosler, Susan - ETSU
31   Howard, Robert - Tri Cities Christian School,TN
32   Huang, Janice - ETSU
33   Jablonski, Tod - ETSU
34   Jackson, Bobby - Pellissippi State Technical C.C.,TN
35   Johnson, Patches L. - Emory and Henry College,VA
36   Kauffman, Joby - Northeast State Technical C.C.,TN
37   Kelly, Holly - Addison Wesley
38   Kerley, Lyndell   -ETSU
39   Kim, Hyungjoong - Univ. of Tennessee
40   Knisley, Jeff - ETSU
41   LaVoie, Scott - ETSU
42   Lertwachara, Kaveephong   -Louisiana Tech University

43   Machida, Motoya - Tennessee Technological University
44   Mateo, Zenaida F. - James Madison University,VA
45   Maxson, Bill - Walters State C.C., TN
46   McLean, James - ETSU
47   Melfi, Vicent F.-   Michigan State University
48   Molinsky, Michael   -Tennessee Wesleyan College
49   Moneyhun, Kay - Walters State CC, TN
50   Moneyhun, Laura - Rutledge High School,TN
51   Narkawicz, Melaine - Tusculum College,TN
52   Narkawicz, Tony - Tusculum College,TN
53   Patch, Steve - University of North Carolina
54   Paulling, John - Tusculum College,TN
55   Pfenning, Nancy - University of Pittsburg
56   Pineda, Aurora - U.N.M. de San Marcos,Peru
57   Polson, Michael - ETSU
58   Poor, Geoffrey - Dalton State College, GA
59   Poteat, Mary Ella - North East Technical CC
60   Preston, Scott - SUNY Oswego,NY
61   Preston, Mary Ann - Oswego County BOCES,NY
62   Price, Robert - ETSU
63   Prior, Tom - ETSU
64   Pumariega, JoAnne   - ETSU
65   Rayburn, William - Austin Peay State,TN
66   Rayburn, Nell - Austin Peay State,TN
67   Renier, Carol - Pellissippi State Technical C.C.,TN
68   Rogove, Joseph - Duxbury
69   Rucker, Jeffrey-   W.H.Freeman
70   Rush, Melody-   ETSU
71   Seier, Edith - ETSU
72   Stevens, Daryl - ETSU
73   Symons, Michael - University of North Carolina
74   Talla, Alain - ETSU
75   Thornhill, Jerry - Southwest Virginia C.C.,VA
76   Trent, Malissa - Northeast State Technical C.C.,TN
77   Tudor, Gail - University of North Carolina
78   Unseren, Michael - Pellissippi State Technical C.C.,TN
79   Utts, Jessica - University of California, Davis CA
80   Ward, Angela - North Greenville College, SC
81   West, Russell - ETSU
82   Wheeler, M. Carl - Pellissippi State Technical C.C.,TN
83   Whitlock, Cathy - University of North Carolina,
84   Wu, Tiejan - ETSU

ABSTRACTS of Short Talks and Posters

Strategies for teaching confidence interval
Scott Preston - State University of New York - SUNY Oswego, New York
The recent issue of the Journal of Statistics Education (V10N03) includes a collection of articles devoted to statistical literacy. The authors have admirable goals and, much to their credit, produce a number of worthy illustrations of assessment strategies. The confidence interval is one of the culminating points of many introductory statistics courses; in my talk I’ll discuss some of my experiences working to help concrete thinkers achieve fluency with confidence intervals. In particular, I’ll demonstrate some strategies for leading students to concern themselves less with formulas, and to give them a successful framework to discover how confidence intervals work and, consequently, succeed at assessments.

FreeCell, Students and Statistics
Paul Baker- Catawba College- Salisbury, North Carolina
The Windows-ubiquitous computer game FreeCell gives rise to some fairly sophisticated statistical questions. Since most students are acquainted with FreeCell and enjoy computer games, it’s possible to sneak in some fairly sophisticated statistics without great pain to the teacher or the student. As they play FreeCell, students can be guided to investigate empirical probability versus theoretical probability, expected values, random distributions, the Central Limit Theorem and
hypothesis testing. Motivated by FreeCell, students seem to understand these concepts better than when taught using traditional teaching methods.

Sampling Experiments for Teaching Statistics
Dana Quade and Michael J Symons- Department of Biostatistics-School of Public Health
University of North Carolina - Chapel Hill, North Carolina 27599-7420

        In-class, real-time sampling experiments are effective and well received by students in our statistics classes. A demonstration is described together with some other example populations for similar sampling.
        Teaching points achieved by this exercise include: (1) illustration of key concepts: a random variable, random numbers, and random sampling; (2) bias with judgement samples; (3) the unbiasedness of random sampling; (4) the decrease in variance of the sample mean with increasing sample size and hence, the plausibility of the variance of a sample mean being the variance of the individual observations divided by the sample size; and (5) the predictable distributional pattern assured by the Central Limit Theorem. Other topics which could be similarly well-punctuated by concrete simulations are the coverage of confidence intervals and the reality of Type I and Type II errors.
        The time required by these demonstrations is five to ten times that of a lecture using overheads or a blackboard. However, the student interest in live demonstrations is greater, and we think their grasp of the point(s), and their retention of them, is also greater with their participation than when we deliver them in a traditional lecture. As valuable as these demonstrations seem to be, the number of them in a course must be balanced against the desired breadth of topics to be covered.

Our Experience in Group Projects
Hasan Hamdan and Arlene R. Casiple - James Madison University- Harrisonburg, Virginia
The importance of computer projects in an elementary statistics course is addressed. The choice between group and individual projects is also discussed. In case the group projects are preferred, the following questions are investigated: how do we form the groups? what is a good group size? What guarantees that everyone in the group is doing his/her share? How do the size and nature of group projects differ from the size and nature of individual projects? Are the expectations the same? Finally; how do we evaluate the performance of computer projects? We also address some future plans for quantitative studies.

A statistics application software in Java-
Kevin R. Doheny- Dalton State College - Dalton, Georgia.
DSC Stats, a Java application software, is limited functionality software for an introductory statistics course. It can compute (for 3 < N < 1001) the average, sample and population standard deviations, quartiles, and maximum and minimum values of a data set. Also, a one variable z- or t-test can be performed. The software also allows for manipulation of the data set or multiple data sets (up to 256 sets), such as sorting, moving, and stacking. Random data sets can be generated (uniform and normal distribution). The interface consists of a text editor atop a spreadsheet. The text editor can open, edit, and save text files. The spreadsheet opens and saves tables with space and tab delimited text, and allows editing. The software was written with a grant, and is free for download, use, and editing

The Cave Project – Teaching introductory statistics in an 'active- learning/computer-enhanced' environment.
Robert Price Jr. , Edith Seier - East Tennessee State University, Johnson City, TN
Recently, thanks to an NSF grant, a new computer classroom ('The StatCave') for the teaching of introductory statistics has been implemented. Due to the large number of sections, most sections meet twice a week, one in the 'Cave' (decorated with especially prepared statistical posters) and one in the 'Mansion' (a regular classroom accross the hall from the Cave). The organization of the StatCave and the 'spider web' (training, communication among instructors, the Resource Center, Web page for students, worksheets, etcetera) that surrounds the Cave will be discussed.

Using a NSF- CCLI Grant to Improve Instruction in Introductory Statistics.
Cathy Witlock, , Dot Sulock and Steve Patch
University of North Carolina at Asheville – Asheville, North Carolina
The statistics department at UNCA wrote and received an NSF grant 3 years ago to build a computer classroom for use by both introductory and upper level statistics classes. We will discuss both the grant writing process and the ways in which our curriculum and teaching methodology have changed since we started using the computer classroom. Members of the committee who wrote the grant will share the details of the proposal process including their handling of the budget and the equipment selected. Instructors who have been using the new classroom will discuss testing, computer based projects, and other opportunities and challenges that have arisen since we started using the new lab.

Experiences from an Online Introductory Level Biostatistics Course - What Does and Does Not Work
Gail Tudor - University of North Carolina - Chapel Hill, North Carolina.
Just as students learn to transition their learning and studying style from a traditional style classroom to an online classroom, so must the professors alter their own styles and tools when it comes to teaching an online course. This presentation will present what one professor has learned over eight semesters of teaching a completely online introductory level Biostatistics course to undergraduates and graduate students, both residential and distance learners. Such topics as the use of audio slides and written notes; evaluations, quizzes and exams; cheating; small and large group communication, use of new technology, teaching software online, and time commitments will all be discussed. This presentation will concentrate on what works and what does not work from students’ perspectives and from the professor’s perspective.

Comparison of Streaming Media Technology for the classroom
Michael Allen - Tennessee Technological University - Cookeville, Tennessee
Many of today's classrooms are now dustless because of the use of whiteboards. But, they are also becoming deskless. With the latest technology, instructors are now able to teach online using internet based distance learning techniques in realtime. In this talk I will present some of the latest innovations in distance learning and streaming media and discuss some of the problems and pitfalls associated with this technology. Examples of such innovations include Mimioboard, Eluminate and Presenter One.

Developing an introductory statistics course with R
Motoya Machida - Tennessee Technological University - Cookeville- Tennessee
In a recent trend of the freeware movement I decided to use R in teaching an introductory statistics course.
R is a statistical computing environment, and often referred to as the reeware version of S-plus.
In this poster session I plan to present sample course materials, including a demonstration (using a computer projector) and a course booklet.

Sampling Simulators for Use in the Introductory Statistics Classroom.
Mary Ella Poteat and Malissa Trent -Northeast State Technical Community College, Blountville, TN

For our introductory statistics course, we have found that the use of a hands-on sampling simulator enables our students to visualize distributions and to discover basic rules of probability.We use a professional bead box, which is typically utilized in industrial quality control. However, the same types of experiments can also be performed with very inexpensive materials. Our poster presentation will contain suggestions for creating sampling simulators and examples of classroom activities.

myJavaStat: an Environment for Teaching Statistics
E. James Harner - West Virginia University- Morgantown, West Virginia

myJavaStat is a Java program that provides a simulation-based approach to teaching statistics. This allows the student to specify the underlying probability model for a problem, to choose the statistic of interest, and to choose the event of interest. myJavaStat also provides a highly interactive environment for doing statistical data analyses. myJavaStat communicates with a Java servlet to retrieve data and student information and to save exercise and quiz answers in a remote database. An R-based backend assessment system is planned.

Partial support for this conference came from an Instructional Development Grant from the Teaching and Learning Center at East Tennessee State University.