Conference Program Home
My Program
All Times EDT
Legend:
CC = Walter E. Washington Convention Center M = Marriott Marquis Washington, DC
* = applied session ! = JSM meeting theme
Activity Details
2 * !
Sun, 8/7/2022,
2:00 PM -
3:50 PM
CC-202A
Emerging Methods in Quantum Computing, Quantum Information, and Quantum Statistical Learning — Invited Papers
Section on Statistical Computing , Section on Statistical Learning and Data Science, Section on Statistics and Data Science Education
Organizer(s): Ping Ma, University of Georgia
Chair(s): Ping Ma, University of Georgia
2:05 PM
Wavelet Matrix Operations and Quantum Transforms
Zhiguo Zhang, University of Electronic Science and Technology of China; Mark Kon, Boston University
2:35 PM
Statistical Computing Meets Quantum Computing
Wenxuan Zhong, University of Georgia ; Yuan Ke, University of Georgia; Ping Ma, University of Georgia
3:05 PM
The Role of Statistics in Quantum Computation and Quantum Information
Yazhen Wang, University of Wisconsin-Madison
3:25 PM
Floor Discussion
27
Sun, 8/7/2022,
2:00 PM -
3:50 PM
CC-140A
SPEED: Statistical Learning and Data Challenge Part 1 — Contributed Speed
Section on Statistical Learning and Data Science , Section on Bayesian Statistical Science, Section on Statistics and Data Science Education
Chair(s): Dena M Asta, The Ohio State University
2:05 PM
Exploratory Analysis of Racial Representation in American Home Ownership
Jhonatan Jorge Medri Cobos, University of South Florida ; Tejasvi Channagiri, University of South Florida
2:10 PM
Examining Relationships Between Household Conditions and Educational Outcomes at the District Level
Erin Walker Post, The University of Iowa
2:15 PM
Public Transit Policies to Promote Equitable Urban Mobility
Jenny Y Huang, Duke University ; Gaurav Rajesh Parikh, Duke Kunshan University; Albert Sun, Duke University
2:20 PM
LinCDE: Conditional Density Estimation via Lindsey's Method
Zijun Gao, Stanford University ; Trevor Hastie, Stanford University
2:25 PM
Quantifying Estimation Error of Nonlinear Kalman-Type Filters
Shihong Wei, The Johns Hopkins University ; James Spall, The Johns Hopkins University
2:30 PM
Random Forest for Individualized Treatment Regimes in Observational Student Success Studies
Juanjuan Fan, San Diego State University ; Luo Li, San Diego State University; Richard A Levine, San Diego State University
2:35 PM
Stochastic Gradient Descent for Estimation and Inference in Spatial Quantile Models
Gan Luan, New Jersey Institute of Technology; Jimeng Loh, NJIT
2:40 PM
Popularity Adjusted Block Models Are Generalized Random Dot Product Graphs
John Koo, Indiana University ; Minh Tang, North Carolina State University; Michael Trosset, Indiana University
2:50 PM
Extrapolation Control Using K-Nearest Neighbors
Kasia Dobrzycka, North Carolina State University ; Jonathan Stallrich, North Carolina State University; Christopher M. Gotwalt, SAS Institute
2:55 PM
A Continual Learning Framework for Adaptive Defect Classification and Inspection
Wenbo Sun, University of Michigan Transportation Research Institute ; Raed Al Kontar, University of Michigan; Judy Jin, University of Michigan; Tzyy-Shuh Chang, OG Technology
3:00 PM
HODOR: A Two-Stage Hold-Out Design for Online Controlled Experimentation on Networks
Nicholas Alfredo Larsen, North Carolina State University ; Jonathan Stallrich, North Carolina State University; Srijan Sengupta, NCSU
3:05 PM
Utilizing Open Source Resources to Teach Introductory Data Science
Tyler George, Cornell College
3:10 PM
Fast Bayesian Estimation for Ranking Models
Michael Pearce, University of Washington
3:15 PM
Diversity in Project-Based Learning Strategy in Undergraduate Statistics Education
Shurong Fang, John Carroll University ; Lisa Dierker, Wesleyan University
3:20 PM
Incorporating Cultural Context in Statistics Courses Through Presentation of Music Videos Before Class
Thomas R. Belin, UCLA Department of Biostatistics
3:25 PM
Boosting Students' Programming Interest Using an R Shiny Web App Rstats in Introductory Statistics Courses
Xuemao Zhang, East Stroudsburg University
3:30 PM
Student Perceptions on Reproducible Research in Introductory and Advanced Statistics Courses
Nicholas W Bussberg, Elon University
3:35 PM
Changes in Undergraduate Attitudes Towards Statistics After Working as Statistical Consultants
Tracy Morris, University of Central Oklahoma; Tyler Cook, University of Central Oklahoma ; Cynthia Murray, University of Central Oklahoma
3:40 PM
Floor Discussion
49 * !
Sun, 8/7/2022,
4:00 PM -
5:50 PM
CC-149AB
Professional Strategies in Statistics: Mentoring Students for Professional Success — Invited Panel
Caucus for Women in Statistics , Justice Equity Diversity and Inclusion Outreach Group, Section on Statistics and Data Science Education
Organizer(s): Julia L Sharp, Colorado State University
Chair(s): Julia L Sharp, Colorado State University
4:05 PM
Professional Strategies in Statistics: Mentoring Students for Professional Success
Panelists:
Brittney Bailey, Amherst College
Emily H Griffith, North Carolina State University
Jo Hardin, Pomona College
Renee Moore, Drexel University
Venessa Singhroy, Queensborough Community College
5:40 PM
Floor Discussion
68
Sun, 8/7/2022,
4:00 PM -
5:50 PM
CC-204C
Fostering Growth in Data Science and Analytics — Contributed Papers
Section on Statistics and Data Science Education
Chair(s): Joan Combs Durso, Duke University
4:05 PM
Developing a Learning Map for Introductory Statistics
Jennifer Kaplan, Middle Tennessee State University; Angela Broaddus, Benedictine College; Dionne Maxwell, Walton School District; Heidi Hulsizer, Benedictine College
4:20 PM
Effective Mentoring: A Guideline to Train a New Generation of Statistician
Presentation
Suhwon Lee, University of Missouri
4:35 PM
The Importance of Workflow as a Topic in Data Science Education
Hunter Glanz, California Polytechnic State University
4:50 PM
Growth in Analytics Jobs in the Last One, Two, and Four Years
Jacqueline Johnson, SAS Institute
5:05 PM
Lessons from Creating a New Analytics Major and a Lynchpin Course During a Pandemic
Penelope S. Pooler Eisenbies, Syracuse University
5:20 PM
Analytics for the Masses: Teaching Data Science Driving vs. Data Science Engineering
Thomas Fisher, The University of Miami - Ohio ; A. John Bailer, Miami University
5:35 PM
Using Six Sigma to Increase a College Campus's COVID-19 Daily Symptom Monitoring
Presentation
Diane Evans, Rose-Hulman Institute of Technology ; Megan Korbel, Milwaukee Tool
72
Sun, 8/7/2022,
4:00 PM -
4:45 PM
CC-Hall D
SPEED: Statistical Learning and Data Challenge Part 2 — Contributed Poster Presentations
Section on Statistical Learning and Data Science , Section on Bayesian Statistical Science, Section on Statistics and Data Science Education
Chair(s): Dena M Asta, The Ohio State University
01:
Exploratory Analysis of Racial Representation in American Home Ownership
Jhonatan Jorge Medri Cobos, University of South Florida ; Tejasvi Channagiri, University of South Florida
02:
Examining Relationships Between Household Conditions and Educational Outcomes at the District Level
Erin Walker Post, The University of Iowa
03:
Public Transit Policies to Promote Equitable Urban Mobility
Jenny Y Huang, Duke University ; Gaurav Rajesh Parikh, Duke Kunshan University; Albert Sun, Duke University
04:
Are There Home Affordability Hot Spots in the United States?
Dane Korver, NC State University; Maegan Frederick, NC State University; Fang Wu, NC State University
05:
LinCDE: Conditional Density Estimation via Lindsey's Method
Zijun Gao, Stanford University ; Trevor Hastie, Stanford University
06:
Quantifying Estimation Error of Nonlinear Kalman-Type Filters
Shihong Wei, The Johns Hopkins University ; James Spall, The Johns Hopkins University
07:
Random Forest for Individualized Treatment Regimes in Observational Student Success Studies
Juanjuan Fan, San Diego State University ; Luo Li, San Diego State University; Richard A Levine, San Diego State University
08:
Stochastic Gradient Descent for Estimation and Inference in Spatial Quantile Models
Gan Luan, New Jersey Institute of Technology; Jimeng Loh, NJIT
09:
Popularity Adjusted Block Models Are Generalized Random Dot Product Graphs
John Koo, Indiana University ; Minh Tang, North Carolina State University; Michael Trosset, Indiana University
10:
Extrapolation Control Using K-Nearest Neighbors
Kasia Dobrzycka, North Carolina State University ; Jonathan Stallrich, North Carolina State University; Christopher M. Gotwalt, SAS Institute
11:
Changes in Undergraduate Attitudes Towards Statistics After Working as Statistical Consultants
Tracy Morris, University of Central Oklahoma; Tyler Cook, University of Central Oklahoma ; Cynthia Murray, University of Central Oklahoma
12:
A Continual Learning Framework for Adaptive Defect Classification and Inspection
Wenbo Sun, University of Michigan Transportation Research Institute ; Raed Al Kontar, University of Michigan; Judy Jin, University of Michigan; Tzyy-Shuh Chang, OG Technology
13:
HODOR: A Two-Stage Hold-Out Design for Online Controlled Experimentation on Networks
Nicholas Alfredo Larsen, North Carolina State University ; Jonathan Stallrich, North Carolina State University; Srijan Sengupta, NCSU
14:
Utilizing Open Source Resources to Teach Introductory Data Science
Tyler George, Cornell College
15:
Fast Bayesian Estimation for Ranking Models
Michael Pearce, University of Washington
16:
Diversity in Project-Based Learning Strategy in Undergraduate Statistics Education
Shurong Fang, John Carroll University ; Lisa Dierker, Wesleyan University
17:
Incorporating Cultural Context in Statistics Courses Through Presentation of Music Videos Before Class
Thomas R. Belin, UCLA Department of Biostatistics
18:
Boosting Students' Programming Interest Using an R Shiny Web App Rstats in Introductory Statistics Courses
Xuemao Zhang, East Stroudsburg University
19:
Developing Data Science Skills Using Call of Duty Data
Matt Slifko, High Point University
20:
Student Perceptions on Reproducible Research in Introductory and Advanced Statistics Courses
Nicholas W Bussberg, Elon University
92 * !
Mon, 8/8/2022,
8:30 AM -
10:20 AM
CC-201
Teaching Social Justice Through Statistics and Biostatistics: The Case for a DEI-Infused Curriculum — Invited Papers
Section on Teaching of Statistics in the Health Sciences , Justice Equity Diversity and Inclusion Outreach Group, Section on Statistics and Data Science Education, Caucus for Women in Statistics
Organizer(s): Rongwei (Rochelle) Fu (she/her/hers), School of Public Health, Oregon Health & Science University
Chair(s): Byung Park (he/him/his), Knight Cancer institute, Oregon Health & Science University
8:35 AM
DEI Through Community-Engaged Learning
Presentation
Jana Lynn Asher, Slippery Rock University
9:00 AM
Using an Ethics Course as a Gateway to DEI Discussions in Biostatistics
Rebecca Roberts Andridge, The Ohio State University ; Abigail Shoben, The Ohio State University
9:25 AM
Incorporating Data Equity into Biostatistics Curriculum
Rongwei (Rochelle) Fu (she/her/hers), School of Public Health, Oregon Health & Science University ; Meike Niederhausen, OHSU-PSU School of Public Health; Janne Boone-Heinonen, OHSU-PSU School of Public Health; Byung Park (he/him/his), Knight Cancer institute, Oregon Health & Science University; Thuan Nguyen, Oregon Health Science University; Kelly Gonzales, OHSU-PSU School of Public Health; Amber Lin, Oregon Health & Science University; Jodi Lapidus, OHSU-PSU School of Public Health
9:50 AM
Discussant: Scarlett (she/her/hers) L. Bellamy , Drexel University, Dornsife School of Public Health
10:10 AM
Floor Discussion
129
Mon, 8/8/2022,
10:30 AM -
12:20 PM
CC-154A
Improving Data Science Education Infrastructure at Community Colleges, Teaching, and Research Universities — Invited Panel
Section on Statistics and Data Science Education , Section on Teaching of Statistics in the Health Sciences, Council on Undergraduate Research, Caucus for Women in Statistics
Organizer(s): Mine Dogucu, University of California Irvine
Chair(s): Babak Shahbaba, University of California Irvine
10:35 AM
Improving Data Science Education Infrastructure at Community Colleges, Teaching, and Research Universities
Panelists:
Sam Behseta, California State University, Fullerton
Alex Franks, University of California, Santa Barbara
Mariam Salloum, University of California, Riverside
12:10 PM
Floor Discussion
182 *
Mon, 8/8/2022,
2:00 PM -
3:50 PM
CC-154B
Innovations on Teaching Design of Experiments: Active Learning, Data Science, and Computer-Generated Designs — Invited Panel
Section on Physical and Engineering Sciences , Quality and Productivity Section, Section on Statistics and Data Science Education, Caucus for Women in Statistics
Organizer(s): Byran J Smucker, Miami University
Chair(s): David J. Edwards, Virginia Commonwealth University
2:05 PM
Innovative Experimental Design Education: Active Learning, Data Science, and Computer-Generated Designs
Presentation
Panelists:
Byran J Smucker, Miami University
Nathaniel Stevens, University of Waterloo
Jacqueline Asscher, Kinneret College on the Sea of Galilee
Alan Vasquez, UCLA
183 * !
Mon, 8/8/2022,
2:00 PM -
3:50 PM
CC-154A
Fuzzy Clusters: Crossing Boundaries Between Non-Academic and Academic Domains — Invited Panel
ENAR , Section on Statistics and Data Science Education, Council of Emerging and New Statisticians (CENS), Caucus for Women in Statistics
Organizer(s): Arielle K Marks-Anglin, Mathematica Inc.
Chair(s): Arielle K Marks-Anglin, Mathematica Inc.
2:05 PM
Fuzzy Clusters: Crossing Boundaries Between Non-Academic and Academic Domains
Panelists:
Lorin Crawford, Brown University
Branko Miladinovic, Janssen Research & Development
Bonnie Shook-Sa, University of North Carolina - Chapel Hill
Sally C Morton, Arizona State University
Adam J Sullivan, Takeda Pharmaceuticals Company
3:40 PM
Floor Discussion
187 *
Mon, 8/8/2022,
2:00 PM -
3:50 PM
CC-143C
Theory and Methods for Building Successful Data Analyses — Topic Contributed Papers
Section on Statistics and Data Science Education , Business Analytics/Statistics Education Interest Group, Section on Statistical Consulting, Caucus for Women in Statistics
Organizer(s): Roger Peng, Johns Hopkins Bloomberg School of Public Health
Chair(s): Stephanie C Hicks, Johns Hopkins Bloomberg School of Public Health
2:05 PM
Diagnosing Data Analytic Problems in the Classroom
Roger Peng, Johns Hopkins Bloomberg School of Public Health
2:25 PM
Veridical Data Science: Highlighting the Role of Judgment Calls in Data Science Practice and Training
Rebecca Barter, University of California, Berkeley ; Bin Yu, University of California, Berkeley
2:45 PM
Design Thinking: Empirical Evidence for Six Principles of Data Analysis
Lucy D'Agostino McGowan, Wake Forest University
3:05 PM
Optimizing for Impact: Defining Success in Exploratory Data Analysis
Caitlin Hudon, OnlineMedEd
3:25 PM
Reproducibility: You Can Do Data Analysis Without it, but Should You?
Tiffany A Timbers, University of British Columbia
3:45 PM
Floor Discussion
225 *
Tue, 8/9/2022,
8:30 AM -
10:20 AM
CC-154B
Effective Reporting of Statistical Results by Consultants and Collaborators — Invited Panel
Section on Statistical Consulting , Section on Statistics and Data Science Education, International Association for Statistical Education
Organizer(s): Harry Dean Johnson, Washington State University
Chair(s): Steve Simon, P-Mean Consulting
8:35 AM
Effective Reporting of Statistical Results by Consultants and Collaborators
Panelists:
Elaine Eisenbeisz, Omega Statistics
Karen Grace-Martin, The Analysis Factor
Clark Kogan, StatsCraft LLC
Kim Love, QCC Quantitative Consulting and Collaboration
Nayak Polissar, The Mountain-Whisper-Light Statistics and Data Science
10:10 AM
Floor Discussion
228 * !
Tue, 8/9/2022,
8:30 AM -
10:20 AM
CC-152A
Promoting Diversity in Sports Analytics — Invited Panel
Section on Statistics in Sports , Section on Statistics and Data Science Education, Section on Statistical Learning and Data Science, Justice Equity Diversity and Inclusion Outreach Group
Organizer(s): Eric Gerber, CSU Bakersfield
Chair(s): Eric Gerber, CSU Bakersfield
8:35 AM
Promoting Diversity in Sports Analytics
Panelists:
Christien Wright, The Milwaukee Bucks
Sameer Deshpande, UW-Madison
Rebecca Nugent, CMU
Arielle Dror, Zelus Analytics
John Tobias, UNC Charlotte
10:10 AM
Floor Discussion
272 *
Tue, 8/9/2022,
10:30 AM -
12:20 PM
CC-204B
Approaches in Clustering for Analysis of Emerging Data Types — Topic Contributed Papers
Section on Statistical Learning and Data Science , Section on Statistics and Data Science Education, Section on Statistical Computing
Organizer(s): Tanzy Love, University of Rochester
Chair(s): Qiuyi Wu, University of Rochester
10:35 AM
Transformation Mixture Modeling for Skewed Data Groups with Heavy Tails and Scatter
Xuwen Zhu, The University of Alabama ; Volodymyr Melnykov, The University of Alabama; Yana Melnykov, The University of Alabama
10:55 AM
Mixtures of Matrix Variate Contaminated Normal Distributions
Salvatore Daniele Tomarchio, University of Catania; Michael Gallaugher, Baylor University ; Antonio Punzo, University of Catania; Paul David McNicholas, McMaster University
11:15 AM
On Measuring Soft Agreement in Clustering
Jeffrey Andrews, University of British Columbia Okanagan ; Ryan Browne, University of Waterloo; Chelsey Hvingelby, Concordia University
11:35 AM
Uncovering Biological Heterogeneity via Clustering to Identify Gene Expression Networks and Patient Similarity Networks
Anjali Silva, University of Toronto
11:55 AM
Discussant: Tanzy Love, University of Rochester
12:15 PM
Floor Discussion
276 * !
Tue, 8/9/2022,
10:30 AM -
12:20 PM
CC-151A
Transforming Higher Education to Achieve Equity — Topic Contributed Panel
Section on Statistics and Data Science Education , Justice Equity Diversity and Inclusion Outreach Group, Committee of Representatives to AAAS, ASA Caucus of Academic Representatives, Caucus for Women in Statistics
Organizer(s): Julia L Sharp, Colorado State University
Chair(s): Sastry Pantula, California State University - San Bernardino
10:35 AM
Transforming Higher Education to Achieve Equity
Panelists:
Julia L Sharp, Colorado State University
Shirley Malcom, AAAS
Abbe Herzig, TPSE
12:10 PM
Floor Discussion
284
Tue, 8/9/2022,
10:30 AM -
12:20 PM
CC-156
Assessment Tools in Statistics and Data Science Education — Contributed Papers
Section on Statistics and Data Science Education
Chair(s): Emily Slade, University of Kentucky
10:35 AM
Three Cognitive Science Principles Every Stats Teacher Should Know
Ross Metusalem, JMP Statistical Discovery
10:50 AM
I Love Data Science! Do My Students? Let’s Measure It!
Presentation
Michael Posner, Villanova University ; April Kerby-Helm, Winona State University; Alana Unfried, CSU Monterey Bay; Douglas Whitaker, Mount Saint Vincent University; Marjorie Bond, Monmouth College; Leyla Batakci, Elizabethtown College
11:05 AM
Measuring Statistics and Data Science Attitudes: A Modern Approach, and Why You Should Get Involved
Presentation
Alana Unfried, CSU Monterey Bay ; Douglas Whitaker, Mount Saint Vincent University; Marjorie Bond, Monmouth College; Leyla Batakci, Elizabethtown College; April Kerby-Helm, Winona State University; Michael Posner, Villanova University
11:20 AM
What Do Instructors Think About Teaching Statistics?
Marjorie Bond, Monmouth College ; Leyla Batakci, Elizabethtown College; Michael Posner, Villanova University; Douglas Whitaker, Mount Saint Vincent University; April Kerby-Helm, Winona State University; Alana Unfried, CSU Monterey Bay
11:35 AM
The Role of Context in Developing Statistics Assessment Items
Laura Ziegler, Iowa State University ; Jennifer Kaplan, Middle Tennessee State University; Angela Broaddus, Benedictine College
11:50 AM
Towards a Data Science Competency Framework for Teaching Future Employees of Official Statistics
Monika Rozkrut, University of Szczecin ; Malgorzata Ludmi?a Tarczynska-Luniewska, University of Szczecin; Dominik Antoni Rozkrut, Statistics Poland
12:05 PM
Tensions in Student Thinking About Statistical Design
Presentation
Kelly Findley, University of Illinois at Urbana-Champaign ; Brein Mosely, University of Illinois at Urbana-Champaign
313 * !
Tue, 8/9/2022,
2:00 PM -
3:50 PM
CC-151B
Teaching Statistical Communication — Invited Papers
Section on Statistics and Data Science Education , Caucus for Women in Statistics
Organizer(s): Shonda Kuiper, Grinnell College
Chair(s): Matt Hayat, Georgia State University
2:05 PM
Audiences and Arguments: Teaching the Strategies of Effective Data Communicators
Presentation
Sara Stoudt, Bucknell University
2:25 PM
What 'Counts' as Statistical Communication?
Amelia McNamara, University of St Thomas
2:45 PM
Data Space: Using Data and Stories to Bring Disciplines Together
Shonda Kuiper, Grinnell College
3:05 PM
Argument Scaffolding: A Template for Quick and Effective Communication
Presentation
Jonathan Auerbach, George Mason University ; Regina Nuzzo, Gallaudet University
3:25 PM
Discussant: Regina Nuzzo, Gallaudet University
3:45 PM
Floor Discussion
362 *
Wed, 8/10/2022,
8:30 AM -
10:20 AM
CC-149AB
Causal Inference for Undergraduates: Teaching Correlation Does Not Imply Students Understand Causal Inference — Invited Papers
Section on Statistics and Data Science Education , Section on Teaching of Statistics in the Health Sciences, ASA-MAA Joint Committee on Undergraduate Statistics, Caucus for Women in Statistics
Organizer(s): Kelly McConville, Harvard University
Chair(s): Kelly McConville, Harvard University
8:35 AM
Covariate Balance as Paramount to Causal Inference
Kari Lock Morgan, Penn State University
9:00 AM
Ideas, Challenges, and Opportunities to Develop Causal Thinking in Undergraduate Statistics
Kevin Cummiskey, West Point
9:25 AM
Causal Inference Throughout the Statistics Curriculum
Presentation
Leslie Myint, Macalester College
9:50 AM
Discussant: Jeff Witmer, Oberlin College
10:15 AM
Floor Discussion
442
Wed, 8/10/2022,
10:30 AM -
12:20 PM
CC-Hall D
Contributed Poster Presentations: Section on Statistics and Data Science Education — Contributed Poster Presentations
Section on Statistics and Data Science Education , Text Analysis Interest Group
Chair(s): Gyuhyeong Goh, Kansas State University
37:
Time to War in the Thucydides Trap
Jake Tan, Wissahickon High School ; Chris McDaniels, Wissahickon High School
38:
Selective Inference in Practice
Anni Hong, Carnegie Mellon University - Statistics dept. ; Arun K Kuchibhotla, Carnegie Mellon University
39:
Resiliency of a Project-Based Statistics Curriculum in the Face of COVID-19 and Online Learning
Robin Donatello, California State University, Chico ; Courtney Merrick, California State University, Chico; Lisa Dierker, Wesleyan University
40:
Foundations for NLP-Assisted Formative Assessment Feedback for Short-Answer Tasks in Large-Enrollment Classes
Susan Lloyd, The Pennsylvania State University ; Matthew Beckman, The Pennsylvania State University; Dennis Pearl, Pennsylvania State University; Rebecca Passonneau, The Pennsylvania State University; Zhaohui Li, The Pennsylvania State University; Zekun Wang, The Pennsylvania State University
41:
Teaching Students in Statistics Courses to Read Critically
Lisa W. Kay, Eastern Kentucky University ; Jill Parrott, Eastern Kentucky University
465 !
Wed, 8/10/2022,
2:00 PM -
3:50 PM
CC-154B
Being Human in Statistics and Data Science: Humanistic Pedagogical and Curricular Innovations — Invited Panel
Justice Equity Diversity and Inclusion Outreach Group , Section on Statistics and Data Science Education, Committee on Statistics and Disability
Organizer(s): Shu-Min Liao, Amherst College
Chair(s): Samuel Echevarria-Cruz, Austin Community College District
2:05 PM
Being Human in Statistics and Data Science: Humanistic Pedagogical and Curricular Innovations
Panelists:
Emma Benn, Icahn School of Medicine at Mount Sinai
Donna LaLonde, ASA
Felicia Simpson, Winston-Salem State University
Rebecca Wong, West Valley College
Shu-Min Liao, Amherst College
3:40 PM
Floor Discussion
466
Wed, 8/10/2022,
2:00 PM -
3:50 PM
CC-149AB
Teaching in the Health Sciences: Is There a Viable Teaching Career Pathway? — Invited Panel
Section on Teaching of Statistics in the Health Sciences , Section on Statistics and Data Science Education, Committee on Career Development
Organizer(s): Ann M Brearley, University of Minnesota
Chair(s): Amy S Nowacki, Cleveland Clinic
2:05 PM
Teaching in the Health Sciences: Is There a Viable Teaching Career Pathway?
Panelists:
Matt Hayat, Georgia State University
Steve Grambow, Duke University
Steve Foti, University of Florida
Matt Zawistowski, University of Michigan
Amanda Ellis, University of Kentucky
James Odei, Ohio State University
3:40 PM
Floor Discussion
471 !
Wed, 8/10/2022,
2:00 PM -
3:50 PM
CC-154A
New Frontier in Developments of Complex-Structured High-Dimensional Data Analysis — Topic Contributed Papers
International Chinese Statistical Association , IMS, Section on Statistics and Data Science Education
Organizer(s): Chenlu Ke, Virginia Commonwealth University; Jiaying Weng, Bentley University
Chair(s): Chenlu Ke, Virginia Commonwealth University
2:05 PM
Functional Group Lasso with Functional Predictor Selection
Jun Song, Korea University ; Ali Mahzarnia, UNC Charlotte
2:25 PM
Testing the Linear Mean and Constant Variance Conditions in Sufficient Dimension Reduction
Yuexiao Dong, Temple University
2:45 PM
Pseudo Sufficient Dimension Reduction with Ill-Conditioned Sample Covariance Matrix
Wenbo Wu, The University of Texas at San Antonio
3:05 PM
Subspace Estimation with Automatic Dimension and Variable Selection in Sufficient Dimension Reduction
Jing Zeng, Florida State University ; Qing Mai, Florida State University; Xin Zhang, Florida State University
3:25 PM
Triply Robust Surrogate-and-Model-Assisted Semi-Supervised Transfer Learning
Mengyan Li, Bentley University ; Tianxi Cai , Harvard University ; Molei Liu, Harvard University
3:45 PM
Floor Discussion
485 *
Wed, 8/10/2022,
2:00 PM -
3:50 PM
CC-140A
Innovations in Introductory Statistics — Contributed Papers
Section on Statistics and Data Science Education
Chair(s): Charlotte Bolch, Midwestern University
2:05 PM
Teaching Statistical Inference through a Conceptual Lens: A Spin on Existing Methods with Examples
Mortaza Jamshidian, California State University, Fullerton, Mathematics ; Parsa Jamshidian, UCLA Biostatiatics
2:20 PM
Statistics Education for Graduate Students with Visual Impairment
Presentation
Annabel Li, University of Northern Colorado
2:35 PM
Infusing History of Statistics Readings in an Introductory Statistics Course
Grant Lee Innerst, Shippensburg University
2:50 PM
Creating a STEM-Based Study Abroad Experience in England Featuring the History of Statistics
Elizabeth Johnson, University of Florida ; David Holmes, University of Florida
3:05 PM
Statistical Literacy UNM Math1300: First Year Results
Milo Schield, University of New Mexico
3:20 PM
Projects with Purpose in Introductory Statistics
Kathy Gray, California State University-Chico
3:35 PM
Modeling Architectural Factors and Garden Visibility in Pompeii
Ben N Dyhr, Metropolitan State University of Denver ; Summer Trentin, Metropolitan State University of Denver; Janae Bacca, Metropolitan State University of Denver
492 * !
Thu, 8/11/2022,
8:30 AM -
10:20 AM
CC-150B
Why Probability, Then Statistics When It Can Be Probability, for Statistics? New Approaches for Teaching Mathematical Statistics — Invited Papers
Section on Statistics and Data Science Education , Section on Statistical Learning and Data Science, International Association for Statistical Education
Organizer(s): Peter E. Freeman, Carnegie Mellon University
Chair(s): Nicholas Joseph Seewald, Johns Hopkins Bloomberg School of Public Health
8:35 AM
Utilizing Spiral Learning to Enhance Conceptual Retention in Mathematical Statistics
Presentation
Peter E. Freeman, Carnegie Mellon University
8:55 AM
Three-Course Dinner or Thanksgiving Feast? Putting the Pieces Together in a Modern Math/Stat Sequence
Randall Pruim, Calvin University
9:15 AM
Teaching Probabability Theory in the Inverted Style
Jonathan Wells, Reed College
9:35 AM
Calcu Less - Compute More: Rethinking Traditional Pathways for Increasing Access to Data Science
Ayona Chatterjee, Cal State Univ East Bay
9:55 AM
Cutting Through the Theory: Emphasizing and Assessing Conceptual Understanding in Mathematical Statistics
Presentation
Erin Blankenship, University of Nebraska-Lincoln ; Jennifer Green, Michigan State University
10:15 AM
Floor Discussion