Publications: Statistics Living-Learning Community


Publications by STAT-LLC students and/or related to the STAT-LLC

Students from the STAT-LLC are indicated with one asterisk (*).
Mentors from the STAT-LLC are indicated with two asterisks (**).
  1. Manjie Fu*, Lingsong Zhang**, Azza Ahmed, Karen Plaut, David M. Haas, Kinga Szucs, and Theresa M. Casey, Does circadian disruption play a role in the metabolic-hormonal link to delayed lactogenesis II? Frontiers in Nutrition, volume 2, number 4 (2015). Journal link; pdf download; 2711 total views of the journal article link from Frontiers in Nutrition, as of February 14, 2017.
  2. Mark Daniel Ward**, Learning communities and the undergraduate statistics curriculum (a response to "Mere renovation is too little too late" by George Cobb), The American Statistician, volume 69, posted as online article, in a supplement to issue 4 (2015); pdf download.
  3. J. Hardin, R. Hoerl, N. J. Horton, and D. Nolan, with B. Baumer, O. Hall-Holt, P. Murrell, R. Peng, P. Roback, D. Temple Lang, and M. D. Ward**, Data Science in the Statistics Curricula: Preparing Students to "Think with Data," The American Statistician, volume 69, pages 343--353 (2015); pdf download.
  4. Ashley Peterson* and Emily Martin* (faculty sponsor: Mark Daniel Ward**), Filling in the Gaps: Using Multiple Imputation to Improve Statistical Accuracy, Rose-Hulman Undergraduate Mathematics Journal, volume 17, issue 2, article 11, 25 pages (2016); pdf download.
  5. Mark Daniel Ward** and Ellen Gundlach, Introduction to Probability (Freeman, 2015), book homepage.
  6. Mark Daniel Ward**, Building Bridges: The Role of an Undergraduate Mentor, The American Statistician, accepted for publication, to appear in 2017.
  7. Weston Phillips*, Peter Boyd* (faculty sponsor: Michael Baldwin**), Predicting Surface Temperatures of Roads: Utilizing a Decaying Average in Forecasting, Journal of Purdue Undergraduate Research, volume 6, pages 9--15 (2016); pdf download.
  8. Peter Boyd*, A Longer Survey is Not Necessarily a Better Survey: A Time Series Analysis. Internal report written and submitted during Procter and Gamble internship, 2016.
  9. Peter Boyd*, Cluster Analysis: A New Perspective on Product Ratings. Internal report written and submitted during Procter and Gamble internship, 2016.
  10. Peter Boyd*, Introduction to RStudio: Statistical Analysis Methods. Internal report written and submitted during Procter and Gamble internship, 2016.
  11. Peter Boyd* and Robert Swihart**, The Effect of Traffic on Denali Wildlife Sightings: A Statistical Analysis. Preliminary report has been submitted, and the final version of the report is forthcoming soon; this is a report to Denali National Park.
  12. David Banks and Mark Daniel Ward**, Advice for Those Applying to Graduate School, Amstat News, issue 464, 31-33, Feb. 2016, pdf download.
  13. K. Das, M. Jackson, S. Keller, D. LaLonde, S. Shipp, J. Utts, and M. D. Ward**, ASA Receives Grant to Establish Series of REUs, Amstat News, issue 466, 20-21, Apr. 2016, pdf download.
  14. Mark Daniel Ward**, Peer-to-Peer Mentoring: How It Fits into the Statistics Living Learning Community at Purdue, Amstat News, issue 471, 28-31, Sep. 2016, pdf download, or online version.
  15. Donna LaLonde and Mark Daniel Ward**, Active Learning Focus of CBMS Joint Statement, Amstat News, issue 477, 26, Mar. 2017, pdf download, or online version.
Posters by STAT-LLC students

Students from the STAT-LLC are indicated with one asterisk (*).
Mentors from the STAT-LLC are indicated with two asterisks (**).
  1. Peter Boyd*, Brian Kidd*, Christopher Vincent*, Weston Phillips*, NFL Playoffs: A Probability Model with Simulations, Undergraduate Research and Poster Symposium, April 12, 2016. Journal paper submitted and currently under review.
  2. Felix Francisco-Sanchez*, McKeith Pearson II, Michael Young, Walid Sharabati, and R. Claudio Aguilar**, Classifying Yeast Cell Phenotypes Using Cell Morphology, Student Poster Session in Discovery Park at Purdue University, April 21, 2016.
  3. Patrick Gallagher*, Bruce A Craig**, Tim Luttermoser, and Grzegorz Buczkowski, Paired Competition Analysis using Mixed Models, Undergraduate Research and Poster Symposium at Purdue University, April 12, 2016.
  4. Patrick Gallagher*, Bruce A Craig**, Tim Luttermoser, and Grzegorz Buczkowski, Paired Competition Analysis using Mixed Models, Conference on Applied Statistics in Agriculture at Kansas State University, May 3, 2016.
  5. Karly Rushmore, Aaron Brehm*, Laura E. D'Acunto, and Patrick Zollner**, Investigating the Impact of Local Versus Landscape-Level Variables on Bat Species Occupancy in Indiana, 8th Annual Midwest Bat Working Group meetings at The Ohio State University, April 21, 2016.
Student conference talks and presentations arising from the STAT-LLC

Students from the STAT-LLC are indicated with one asterisk (*).
Mentors from the STAT-LLC are indicated with two asterisks (**).
  1. Felix Francisco-Sanchez*, McKeith Pearson, Michael Young, Walid Sharabati, and R. Claudio Aguilar**, Quantitative Analysis of Yeast Cell Morphology Defects Induced by Gene De-Regulation, hosted on YouTube and presented at the Virtual Brown Bag Research Discussion Series, Center for Science of Information, March 31, 2016.
  2. Sameer Manchanda*, Mikaela Meyer*, and Nan Kong**, On Comprehensive Mass Spectrometry Data Analysis for Proteomic Profiling of Biological Samples, presented at the Symposium on Big Data, Human Health and Statistics, at the University of Michigan, on July 21, 2016.
  3. Sameer Manchanda*, Mikaela Meyer*, Nan Kong**, Qianqian Li, Yan Li, On Comprehensive Mass Spectrometry Data Analysis for Quality Assessment of Biological Samples (Mass Spectrometry Data Analysis for Mass-to-Charge Signature Identification: Applications in Biosample Quality Control), 1 of 7 finalists for the 2016 INFORMS Undergraduate O.R. (Operations Research) Prize Competition, November 13, 2016.
  4. Kent Gauen*, An Overview of Machine Learning using MNIST Dataset, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 23, 2016.
  5. Kent Gauen*, Fundamental Supervised Machine Learning Models, presented at the Symposium on Big Data, Human Health and Statistics, at the University of Michigan, on July 21, 2016.
  6. Abigail Vorhies* and Bailey O'Malley*, Linking Mesodinium Bloom Timing with River Flow Discharge and Estuarine Classification in the Columbia River Estuary, presented in summer 2015 at the NSF Center for Coastal Margin Observation and Prediction, in Portland, Oregon.
  7. Alan Min*, Population Balance Model for DNA Methylation, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 23, 2016.
  8. Karan Samel*, Predicting Advertisement Clicks Using Deep Learning, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 23, 2016.
  9. Kristen Mori* and Jack VanSchaik*, Statistical Soundscape Ecology: Entropy and Phase Transition Analysis of Big Sound Data, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 22, 2016.


This material is based upon work supported by the National Science Foundation under Grant No. 1246818. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.