> ~}M gbjbj== %WWc!l~~~~~~~82Tl7a7c7c7c7c7c7c7$9 ;7~7~~7~~a7a7R&5~~=7PqNphA6=7$707S6x<8x<=7~~~~Beyond the Formula VIII
Constantly Improving Introductory Statistics:
Updating A Crowded Curriculum
Thursday, August 5, 2004
8:00 a.m. Registration Outside Room 3205 ~ Monroe A
Breakfast (juice, coffee, fruit, bagels, muffins) Room 3205 ~ Monroe A
[Thanks to Duxbury Press]
9:00 a.m. Welcome and Introductions Room 3205A ~ Monroe B
Opening Comments and Introductions David McNitt
Welcome Chet Rogalski, Dean, Liberal Arts
Announcements Brigitte Martineau
9:30 a.m. Session 1 Opening Keynote Address Room 3205A ~ Monroe B
S.1 William Harkness, Penn State University Host: David McNitt
Restructuring Intro Stats: Changing the Image of Statistics Part IWhat Should We Teach? In the minds of many students, statistics is a subject to be avoided if at all possible. Last year at this conference Paul Velleman, in his closing keynote, said There is an interesting, subtle, beautiful introductory statistics course (out) there, but it is often obscured by topics, notation, terminology, and tedium that dont belong. We will take a look at how we can (in his words) sculpt the introductory statistics course to make it not only intellectually stimulating but also enjoyable. We will consider the steps that one might follow in redesigning a course that accomplishes both purposes. These include the:
Approach we can adopt
Process to follow
New opportunities
Choice of topics and their priorities
[Refreshments in Room 3205 ~ Monroe A]
10:45 a.m. Session 2 Directed Workshops
S.2.1 Kirk Steinhorst, University of Idaho Host: Dick Stewart Room 12109
Intro stat should not be like drinking water through a fire hose Introductory statistics books have grown larger and larger over the years. There are too many topics and too much detail. The instructor must be ruthless in deciding exactly what must be covered. Many courses struggle because there is too much material. But  what to cut? I present the essential topics that I have refined over the last 30 years from the myriad topics available and justify my choices. The resulting syllabus is slim and trim. Students need to see the big picture and the beauty of introductory statistics. They should not get bogged down in details. I illustrate specific choices that the instructor must make in descriptive statistics, probability, and inference. Statistics does not need to be the most dreaded course. Simplicity is beauty in this case. [Target Audience: All]
S.2.2 Floyd Bullard, NC School of Science & Mathematics Host: Jason Mahar Room 12111
Paper Helicopters: An Extremely Versatile Data Collection Tool In this session we'll look at a paper helicopter first used by George Box to have his students collect data. The helicopter is virtually free and easy for students to make on their own and take with them out of class (and thus they may conduct experiments on their own time). It can be used to collect either numerical or categorical data that can be used for about any kind of inference typical in a firstyear statistics course, including hypothesis tests or confidence intervals comparing means or proportions, chisquare tests, and linear regression.
[Target Audience: All]
S.2.3 Mary Harrison, Virginia Beach City Public Schools Host: Sue Englert Room 11107
Using the TI83/84 in the statistics classroom This session is designed to show how using a TI83/84 calculator will enable the instructor to focus on the meanings of statistical calculations rather than the arithmetic involved in doing the calculations. By the end of the session the participant should be able to enter data and use the calculator to perform basic descriptive statistics for univariate and bivariate variables, calculate probabilities for binomial, geometric and normal distributions, confidence intervals, and tests of inference involving Student's t, z, and chisquare.
[Target Audience: Any instructor who uses Texas Instrument calculators in the classroom  No previous knowledge or experience with Texas Instrument calculators is necessary.]
S.2.4 Brad Hartlaub, Kenyon College Host: Christy Fogal Room 11101
Exposing Students to Statistical Methods Based on Counts and Ranks Far too often students leave an introductory statistics course thinking that statistical inferences are impossible OR very difficult if the normal model is not applicable to the data. With current technology, students can focus on understanding these competing methods based on counts and ranks without getting caught up in all of the nittygritty details. We will focus on onesample and twosample location problems which deal with statistical inferences for population medians rather than population means. If time permits, other problems will be considered.
[Target Audience: All  Prerequisites: Knowledge of basic methods in statistical inference e.g., onesample t test, paired t test, and the twosample ttest;]
12:00 p.m. Lunch Room 3205 ~ Monroe A
1:00 p.m. Session 3 Directed Workshops
S.3.1 Linda Young, University of Florida Host: Peter Collinge Room 12209
Design of Studies: Important Concepts Since the design of a study has a major effect on what conclusions can and cannot be drawn from that study, basic design principles should be included in any introductory course, but which ones and at what depth? During this interactive session, basic design issues, such as the choice of experimental unit, random selection of units from a population, random assignment of treatments to the experimental units, sample size, and power, and their importance (or lack thereof) in an introductory statistics course will be discussed. [Target Audience: All]
S.3.2 Robert Gould, UCLA Host: Cindy Smith Room 12215
INSPIREd: Report on an NSFfunded project to prepare firsttime AP Statistics teachers The AP Statistics exam has grown exponentially since its founding a few years ago. That growth has fueled a strong demand for AP Statistics teachers and yet there are few teachertraining programs for statistics teachers. The INSPIRE program is funded by the NSF and a joint effort between statisticians and statistics educators at the ASA, Cal Poly San Luis Obispo and UCLA to provide a sustained, indepth content course targeting beginning AP Stats teachers. As of this summer, one cohort of teachers has finished the first year (a workshop followed by a distance learning course) and are starting their second year (a "practicum" with a statistician mentor). Meanwhile, a new cohort is beginning the program. I'll discuss the design of the program and critically evaluate its achievements. [Target Audience: HSnon AP, HS AP  No prerequisite]
S.3.3 Carl Lee, Central Michigan University Host: Dick Stewart Room 12205
The Issues of Student Attitudes and Motivations in Introductory Statistics The difficulties in teaching and learning introductory statistics have received considerable attention by educators and professional organizations. Review of the research literature suggests that factors associated with the difficulty may include the cognitive domain on the ability of learning, the affective domain on beliefs and attitudes, and the metacognitive domain on motivation and strategies of learning. There has been considerable amount of attention paid to pedagogical issues of teaching introductory statistics. It typically assumes that through innovative teaching pedagogy, students will be more interested and motivated to learn. However, this assumption may not hold as what educators have originally anticipated. In this presentation, we will turn our attention to the less investigated learning domain, namely, the affect and metacognitive domain. The findings from two studies will be shared. One is an interview study conducted in four different institutions to investigate the issues related to motivations and expectations. The other is a survey study conducted in two institutions for four semesters. We will first share the findings from both studies, discuss the implications on teaching, and then propose some strategies that may be useful for developing active learning environments. [Target Audience: All]
S.3.4 Jason Krasowitz, Minitab, Inc. Host: Kimberley Martello Room 11101
Whats New in Minitab 14 Graphics The graphics in release 14 have been significantly improved, and this class will take you through those changes. Starting with the new graph galleries, users can specify the type of graph they want to create which simplifies subsequent dialog boxes. We will demonstrate how graph editing is now easily done after graphs are created via doubleclicking on an element or selecting it using the new graph editing toolbar. Now, elements such as means, interval bars, or fitted lines can be added to an existing graph, eliminating the need to create duplicate graphs. The improved graph layout tool allows you to quickly plot more than one graph on a page, and specifying subsets of data to use in a graph is now possible using data options in the dialog boxes. Since graphs in Release 14 are now tied to the data, well show you how to update your graphs when data changes, either automatically or manually. There are also some new graphs to version 14, including the Individual Value Plot, and the Empirical Cumulative Distribution plot. Visualize 3D data using our new rotating plots. Other enhancements such as creating similar graphs, duplicating graphs and saving the command language will also be discussed. [Target Audience: All]
[Refreshments in Room 3205 ~ Monroe A]
2:15 p.m. Session 4 Address Room 3205A ~ Monroe B
S.4 G Rex Bryce, Ronald Snee, Roger Hoerl Host: Joe Gallo
A Statistical Thinking Approach to Introductory Statistics: Theory and Practice This session will discuss the prospect of basing introductory statistics courses on statistical thinking, i.e., fundamental concepts of statistics, as opposed to statistical methods or calculations. We begin with an analysis of typical issues in introductory statistics courses, and identify root causes. For example, we suggest that lack of a "big picture view" of what statistics is, and having no means of integrating the various tools into an overall approach to scientific inquiry, naturally leads to student's viewing statistics as a miscellaneous collection of isolated tools. We have found that statistical thinking, with its emphasis on core concepts, can be used to provide this unifying theme, as well as to address several other key issues. After suggesting the use of statistical thinking as the basis of intro courses, we provide data from two actual courses taught using this approach at BYU. These data, both on what was actually done, and how it was received by students, provides significant evidence in favor of this approach.
[This session will also serve as an introduction to the workshop immediately following at 3:30 PM and/or the breakout session on Friday at 10:30 AM.]
[Refreshments in Room 3205 ~ Monroe A]
3:30 p.m. Session 5 Discussion Sessions
S.5.1 Linda Young, University of Florida Room 12207
Sharing Collegiate Concerns This hour provides an opportunity for those teaching at the college level to exchange ideas about the introductory statistics course. In this informal and loosely structured session, participants are encouraged to share efforts that were especially successful or unsuccessful and to identify particular challenges. The importance (or lack of importance) of some of the concepts that are considered optional in this first course will also be explored. [Target Audience: All invited]
S.5.2 Brad Hartlaub, Kenyon College Room 12203
A Snapshot of the AP Statistics Program Brad will compare growth rates in AP Statistics with those in AP Calculus, address general trends on recent exams (including the 2004 exam), and make some recommendations for teachers before a general question and answer session about the AP Statistics Program. Questions regarding curricular issues, course content, the use of statistical software, test development, the exam, rubrics, the annual reading, grade setting, course projects, postexam activities, or professional development opportunities are most welcome.
[Target Audience: All invited  Prerequisite: Interest in AP Statistics]
3:30 p.m. Session 5 Workshops
S.5.3 Ruth Carver, Germantown Academy Host: Mark Harris Room 11104
Using Fathom Dynamic Statistics Software to explore Sampling Distributions, the Central Limit Theorem, Confidence Intervals and the Robustness of the tprocedure We will start with a handson activity to help students understand sampling distributions and the Central Limit Theorem. We will then extend this activity by using the simulation features of Fathom Dynamic Statistics Software to investigate the effect of sample size on the mean and standard error of a sampling distribution. Our original activity will then be extended to constructing and understanding confidence intervals. The simulation features of Fathom will be used as an aid in understanding what can and cannot be said about a particular confidence interval, the meaning of a particular confidence level and the robustness of the tprocedure when conditions involving sample size have not been met. No familiarity with Fathom Dynamic Statistics Software is assumed. Participants will be given a multiplatform disk containing all simulations for use with their students.
[Target Audience: All invited  No reservation needed!  90 minutes]
S.5.4 Roger Hoerl, G Rex Bryce, Ronald Snee Host: Pat Kuby Room 3209 ~ Empire
The Theory Behind A Statistical Thinking Approach This workshop will delve deeper into the use of statistical thinking as the basis for introductory statistics. We begin by discussing the theory underlying a statistical thinking approach to introductory statistics. This theory is based on existing educational and behavioral research. Once this theory is presented, attendees will have the opportunity to raise questions and concerns, and make suggestions for what such a course should look like, and how it should be implemented. Questions and issues that we are unable to discuss in this session will be taken up in the breakout session scheduled for Friday at 10:30 AM.
[Must have registered for this session  105 Minutes]
3:30 p.m. Book Exhibit Room 3130 ~ Forum
4:30 p.m. Open Lab Room 11109
Available for those wishing to use computers to practice new skills, complete workshop projects, or use the Internet.
5:00 p.m. Reception Room 3130 ~ Forum
6:00 p.m. Dinner Room 3205 ~ Monroe A
7:00 p.m. Session 6 After Dinner Address Room 3205 ~ Monroe A
S.6 Peter Holmes, Nottingham Trent University Host: Bob Johnson
Assessment in Statistics: A twoedged swordIt is often asserted that we have to assess students' work in statistics in order to maintain standards. Unfortunately the evidence is that many of the questions we ask and the overemphasis on assessment for qualifications can have the effect of encouraging statistical illiteracy. In this talk I want to look at this problem and consider whether we can learn anything for statistical education from a statistical approach to quality improvement and see how we can use assessment to improve learning.
[Target Audience: HS nonAP, HS AP, 2 yr college & 4 yr college]
Friday, August 6, 2004
8:00 a.m. Breakfast (juice, coffee, fruit, bagels, muffins) Room 3205 ~ Monroe A
Announcements precede each of the Session 7 workshops
8:15 a.m. Announcements Eraj Basnayake Room 3209 ~ Empire
8:40 a.m. Announcements Karen Wagner Room 12209
Announcements Pam Keyes Room 12215
Announcements Michael Wagner Room 12205
8:20 a.m. Session 7 Workshop [8:20 to 10:05 AM] Room 3209 ~ Empire
S.7.4 Carl Lee, Central Michigan University Host: Eraj Basnayake
Planning and Assessing Student Learning Outcomes for Statistics Learning outcomes usually refer to four domains of educational progress and the end results of learning. These four domains are knowledge, skills, affective domains and the domain of values and ethics. Learning outcomes assessment can be conducted at several levels for different learning goals and objectives, which include the institutional level, the college level, the program level and the classroom level. At each level, it is a cycle typically including the planning stage, the implementation stage and the actiontaken stage. It is similar to the Demings PLANDOSTUDYACT quality improvement Cycle, which constantly asks and addresses the two questions: (1) Are we doing the right things, and (b) Are we doing the things right? In this workshop, we will first discuss an assessment framework and address some potential gaps in a typical student learning outcome process based on the framework. The remaining time will focus on the development of an assessment plan at the program level for statistics major and the applications of tools for the classroom assessment for statistics courses. A handson approach will be used to engage each participant to develop his/her own assessment plan and determine the appropriate direct and/or indirect measures for assessing the objectives and to practice some commonly used classroom assessment tools.
[Must have registered for this session  105 Minutes]
8:45 a.m. Session 7 Directed Workshops
S.7.1 Kirk Steinhorst, University of Idaho Host: Karen Wagner Room 12209
Testing and assessing in a modern statistics methods course Modern technology makes statistical computations trivial. However, students need to do some calculations by hand so that they understand what the calculator or computer is doing. How can we assess students' knowledge using appropriate technology? The answer is a combination of the right kind of homework, inclass activities, and takehome/inclass tests. Homework should be conceptual mixed with problems based on real data requiring real calculation. Inclass activities should explore concepts and include simple calculations. The takehome/inclass test consists of problems on which students can collaborate and use the calculator or computer followed by an inclass portion where students use the takehome to answer a series of related or derivative questionsthus being individually responsible in the end. Examples are given of each activity. [Target Audience: All]
S.7.2 Floyd Bullard, NC School of Science & Mathematics Host: Pam Keyes Room 12215
The AP Statistics Curriculum: What's In, What's Out, and Why The normal approximation to the binomial is in, but the continuity correction is out. Linear regression on one variable is in, but multiple regression is out. Simulations are in. Many computations are out. Why were these and other choices made and what kind of curriculum does that produce? In this session we'll examine (though we won't resolve it to everyone's satisfaction!) the underlying question: "What should a student know after completing a firstyear statistics course?" [Target audience: All]
S.7.3 Robert Gould, UCLA Host: Michael Wagner Room 12205
How Statistics differs from Math: beyond mean, median and modeAlthough the intersection between Statistics and Mathematics is quite broad, there is sufficient "extramathematical" content in Statistics to make it challenging for a firsttime statistics teacher. Mathematics provides a wonderful foundation for learning Statistics, but it is not enough. Math teachers preparing to teach statistics will need to master a new set of skills and concepts. I will present some examples of this "extramathematical" content in the context of an epidemiology case study. A subtheme will be the role of software to teach statistics and, in keeping with this subtheme, I will demonstrate the use of Fathom to gain insight into the questions raised by the case study.
[The ideal audience would be beginning statistics teachers trained in mathematics. Beyond that, it is appropriate for All  No prerequisite statements]
[Refreshments in Room 3205 ~ Monroe A]
10:15 a.m. Session 8 Directed Workshops
S.8.1 G Rex Bryce, Roger Hoerl, Ronald Snee Host: Patricia Kuby Room 12209
Open Discussion of Potential Issues With the Statistical Thinking Approach This breakout is intended to be an open, informal, interactive discussion of potential issues with statistical thinking approach to introductory statistics. The first topics of discussion will be issues that were raised in the workshop on this topic earlier in the conference. Issues may relate to the fundamental approach, to the courses actually offered at BYU, or to unique situations at different institutions represented by the attendees. Following this, attendees will have the opportunity to ask additional questions, and make their own suggestions for comment by others. [Open to all.]
S.8.2 Peter Holmes, Nottingham Trent University Host: Jason Mahar Room 12215
Basic Statistics Courses: boring and irrelevant or true and useful? Student reaction to many of our basic introductory statistics courses is often not favourable. There have been many suggestions for changing this and many colleges have introduced new ideas. Maybe we need a radical look at the nature of statistics as used in practice and consider the possibility of different basic courses, with different aims, for different groups of students. This talk raises some different possibilities for discussion.
[No prerequisites and is more relevant to 2 year and 4 year college; less relevant to HS]
S.8.3 Mary Harrison, Virginia Beach City Public Schools Host: Renee Shanly Room 12205
Using the TI89 in the statistics classroom This session is designed to show how using a TI89 calculator will enable the instructor to focus on the meanings of statistical calculations rather than the arithmetic involved in doing the calculations. By the end of the session the participant should be able to enter data and use the calculator to perform basic descriptive statistics for univariate and bivariate variables, calculate probabilities for binomial, geometric and normal distributions, confidence intervals, and tests of inference involving Student's t, z, and chisquare. The 89 has some builtin enhancements over the 83 that will be explored as well.
[Target Audience: Any instructor who uses Texas Instrument calculators in the classroom  No previous knowledge or experience with Texas Instrument calculators is necessary.]
S.8.4 Angel Andreu, Monroe Community College Host: Kim Martello Room 12203
SAT Scores and First Semester GPA (A Case Study) Using the basic statistics taught in an introductory statistics course, we'll try to answer the ageold question of whether SAT scores can predict first semester GPA at a comprehensive community college.
[Target Audience: All]
11:30 a.m. Lunch Room 3205 ~ Monroe A
12:30 p.m. Session 9 Panel Discussion Room 3205A ~ Monroe B
S.9 Linda Young, Panel Leader, with William Harkness, Brad Hartlaub, Peter Holmes
The Ideal Introductory Statistics Course: The Final Touch In this session, the four panelists will briefly provide a summary of the ideas presented at BTF VIII, highlight issues or concepts that may not have been addressed during BTF VIII, and discuss the core purpose or goal of the course. This will be followed by an open discussion between panelists and the audience. Everyone will be encouraged to identify areas that need further development.
[Refreshments in Room 3205 ~ Monroe A]
1:45 p.m. Session 10 Closing Keynote Address Room 3205A ~ Monroe B
S.10 William Harkness, Penn State University Host: David McNitt
Restructuring Intro Stats: Changing the Image of Statistics Part IIHow Should We Teach? If we are to change the currently perceived negative image of the first course in statistics we must also address our approach to teaching it. The research and anecdotal literature indicates that lecturing has a role in the learning process but other approaches may be much more important. We need to transfer responsibility for learning to students and reinvent ourselves as facilitators. We need to make statistics relevant, interesting, and fun. How do we do this (especially if we are not hams!)? In this closing address I will discuss pedagogical techniques that have been found to be effective in promoting successful learning. These include:
Using technology appropriately and efficiently
Using assessment instruments with rapid feedback
Promoting a conducive atmosphere for learning
Sequencing of topics that enhances student understanding
Handson, collaborative group work on activities and projects student surveys generating datasets that are relevant to students
2:45 p.m. Wrapup Pat Kuby & Bob Johnson Room 3205A ~ Monroe B
Completion and Collection of Evaluation Forms
Awarding of Door Prizes
We hope you enjoyed your visit with us, learned a lot and that you return to your home institution ready to enthusiastically apply what you have learned.
We invite you to return next year to BTF IX, Constantly Improving Introductory Statistics: Teaching Techniques  The Why and The How To, Thursday and Friday, August 45, 2005. Visit our website [http://www.monroecc.edu/go/beyondtheformula/] regularly for information about BTF2005. We hope to announce the keynote speaker in September and the rest will be posted as it develops.
Have a safe trip home!
PROGRAM
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