STAT 450 students have worked collaboratively on real case studies brought by researchers from other disciplines. Supervised by the teaching team, STAT 450 students performed various statistical analyses to address their “client’s” questions. Results from six exciting projects are presented in this poster session.
Poster 1: Affirmative Action
Collaborators: Agnes d’Entremont (Mechanical Engineering, UBC), Alison Banka (Chemical Engineering, University of Michigan)
STAT 450 Team: Jiahae Lee, Derek Situ, Anthony Yang
Affirmative action policies in the United States intend to correct disadvantages felt by minorities in education and employment. These policies are now banned in nine states. The purpose of this study is to determine whether affirmative action bans impact the enrolment of white female, non-white female, and non-white male students in college engineering programs in US states that implemented such bans between 2005 and 2020.
Poster 2: Stream Flow
Collaborator: Asad Harris (Earth, Ocean and Atmospheric Sciences, UBC)
STAT 450 Team: Vanessa Bayubaskoro, Anjali Chauhan, Kelvin Li, Kohl Peterson
We develop a model that predicts the annual average streamflow for Canadian watersheds by studying the effects of climate variables on the annual average streamflow to provide crucial information for efficient water resource management. From looking at 23 different watersheds across Canada, we identify important climate variables that affect the average streamflow values of watersheds, predict the average streamflow values and report any unusual abnormalities in the streamflow value that can help in predicting floods and droughts. Our results show that most climatic variables have a linear relationship with streamflow.
Poster 3: Stem Cells
Collaborator: Claudie Roy (L/BMT Program of BC and Department of Medicine, UBC)
STAT 450 Team: Zoe Cao, Shuaib Habib, Yuxin Zhang
Up to one third of potential allogenic hematopoietic stem cell transplantation recipients do not have access to ideal donors (fully HLA-matched donors). For these patients, three alternative donors are available: HLA-Mismatched Unrelated, Haploidentical, or Umbilical Cord Blood donor. The objective of this project is to describe the outcome in allogenic hematopoietic stem cell transplantation with alternative donors by comparing the toxicity profile of patients, finding survival probability, and assessing the incidence of relapse and cause of mortality in patients from the three different alternative donors.
Poster 4: Salmon Mortality
Collaborator: Emma Lunzmann-Cooke (Forest and Conservation Sciences, UBC)
STAT 450 Team: Richard Hou, Andy Lin, Xiaotong Liu, WeiHao Qiu
Fishery managers in catch-and-release fishing face a challenge in developing effective management tools to protect wild salmon populations. This statistical project aims to examine the factors that influence fish survival after a catch-and-release event and make some suggestions on fishing to minimize the mortality rate following the release. In the best-performed logistic regression model, we identify that eye injury, hook location, fin damage, and reflex score are the key factors in predicting fish survival.
Poster 5: Linguistics
Collaborator: Marie-Eve Bouchard (Department of French, Hispanic & Italian Studies, UBC)
STAT 450 Team: Cindy Chen, Jessica Liu
Santomean immigrants are known to have different /r/ sounds than non-immigrant Portuguese speakers. To understand how certain linguistic factors (such as the syllabic tone or the position of the r-sound in the word) affect Santomeans' pronunciation of /r/ sounds, 40 participants were interviewed and relevant linguistic data were collected. We develop and compare multiple models to investigate which are the most influential linguistic factors that affect /r/ sound pronunciation.
Poster 6: Invisalign
Collaborator: Mohyman Sarfraz (Orthodontics, UBC)
STAT 450 Team: Lucas Crichton, Omer Tahir, Shihao Tong
Invisalign First is an orthodontic treatment for children. This study considers orthodontic results for children treated for malocclusion, a specific type of abnormal alignment of the teeth. The goal of this study is to determine how well Invisalign’s Artificial Intelligence methodology predicts the outcome of the treatment.