Research Assistant in Math Program (RAMP)

Goal

The goal of the Research Assistant in Math Program (RAMP) is to create an undergraduate research environment where Biola math and computer science majors are supported in research projects that (i) complement their academic goals and (ii) facilitate department growth, which together further Biola’s mission. RAMP is funded by a visionary donor to the department. Research Assistants (RA’s) through RAMP are paid to assist faculty with research.

RAMP Committee

Joseph Dimuro, Ph.D (Co-Chair)
John Kwak, Ed.D (Co-chair)
Jason Wilson, Ph.D (Secretary)

Funding

Biola is a private, non-profit 501(c)(3), Christian University and does not accept governmental funding. RAMP is supported exclusively through private donors and all donations are tax deductible. We believe that the greater the success of RAMP, the more equipped our students will be to fulfill the biblically mandated mission of Biola University, which is to “equip men and women in mind and character to impact the world for the Lord Jesus Christ.” If you would like to help ‘build the RAMP,’ please go to the financial information page for donation information.

Completed Projects

  1. Joseph Lane (2019). Explaining the 2019 MLB Home Run Record with Quality of Pitch — Although home runs were down in 2018, the 2017 record was smashed in 2019 with further documented changes to the ball. While most commentators overlooked the ball, we showed that the record all time low quality of pitch (QOP) accompanied the home run record. The primary change was found to be location – pulling the ball from the middle of the strike zone to low and inside. Joseph performed calculations for the project, as well as editorial work.
  2. Jeremiah Chuang (2018).  Explaining the 2017 MLB Home Run Record with Quality of Pitch — There was a surge in home runs in major league baseball in 2017 and almost everyone attributed it to changes in the ball, and the batter’s approach to hitting. In this research, we showed that the quality of pitch (QOP) was also a factor. In 2017 QOP was down, primarily due to a decrease in vertical break. Jeremiah performed calculations for the project, as well as editorial work.
  3. Brian Queme; Angela Cuerpo; JT Yarter (2017). Distances to Grocery and Convenience Stores in Low- and High-Income Neighborhoods: A Limiting Factor to Accessing Healthy Foods — Studies have shown that diet related disease is more prevalent in low-income neighborhoods and that there is a relationship between diet related disease and the absence of grocery stores. Twenty-five random GPS residential locations in twelve cities in Los Angeles County were generated, and the distances to the two closest grocery stores (i.e. stores with more than five kinds of fresh fruits and vegetables) and convenience stores were measured. After statistical analysis, it was found that homes in low-income neighborhoods are significantly closer to convenience stores than grocery stores, whereas homes in high-income neighborhoods are closer to grocery stores.
  4. Jeremiah Chuang (2017).  Quality of Pitch (QOP) — Investigations into major league baseball using our Quality of Pitch (QOP) statistic. Does a batter’s handedness influence a pitcher’s QOP? Can the QOP average of a team help predict the likelihood of victory in a major league baseball game?
  5. Pixler (2015). Quality of Pitch (QOP) – Calculating a Single Number to Rate the Quality of a Baseball Pitch — Throughout 2015, Josh Pixler assisted Dr. Wilson in the development of the Quality of Pitch statistic (QOP). Using PITCHf/x data from major league baseball stadiums, they extracted the pitch trajectory, location, and speed, and combined this information into a single number to quantify pitch quality. Joel assisted in the development of the case study on the LA Dodgers 2014 season and accompanied Dr. Wilson to the Society for American Baseball Research where it was presented. See Presenter's List: http://sabr.org/latest/2015-sabr-analytics-conference-research-presentations; See Presentation: Pixler (2015). Quality of Pitch (QOP) – Calculating a Single Number to Rate the Quality of a Baseball Pitch
  6. Molly Foklert (2014). Gospel Inventory Factor Analysis -- In Fall 2013, an inventory to assess Biola student's understanding of the gospel was conducted by Dr. Wilson on a random sample of 110 Biola students. In this work, Molly Folkert performed a Factor Analysis on the data to test Dr. Wilson's hypothesis that the 23 inventory items could be well explained by just three underlying factors. PDF of Paper: A Survey in Factor Analysis.
  7. Sam Britton, Daniel Lundstrom, Joshua Sansonetti (2013). Probabilities of Qwirkle Hand Values  Calculations of the theoretical probabilities of various Qwirkle hands, supported by Monte Carlo simulations of the empirical probabilities.
  8. Jolene Houtsma (Spring 2013). Integration of Faith and Learning Assessment -- In Spring 2012, an inventory to assess the Integration of Faith and Learning was conducted by Dr. Wilson on a random sample of 269 Biola undergraduate students. In Spring 2013, Jolene Houtsma administrated the 12-month follow-up study. Her tasks included organizing and communicating with ten undergraduate volunteers from Dr. Wilson’s classes who contacted the respondents. PDF of Article: Houtsma (2013), Integration of Faith and Learning Assessment.
  9. Jolene Houtsma (Spring 2013) Educational Tolerance -- In Spring 2013, a student of Dr. Patrick Wolf, University of Arkansas College of Education named Albert Cheng selected Biola university as an ideal population to conduct an educational tolerance study. The reason is that we have a sizable population of public, private, and homeschool students, which is uncommon. Mr. Cheng solicited Dr. Wilson’s help in collecting the data. The data collection became a joint effort between volunteers from Dr. Wilson’s statistics classes and his Research Assistant, Jolene Houtsma. The students were: Daniel Chapman, Lauren Chen, SueZen Chew, Sarah Hurlburt, Garret Huckaby, Scarlett Liu, Katie McCusker, Joshua Sansonetti, Maddison Salcido, Chloe Willms, and Samantha Wilson. Jolene administrated the data collection process from start to finish, including data cleaning. See full text article: Houtsma (2013), Educational Tolerance.
  10. Steven Oatey (Fall 2013, Spring 2013) Business As Mission -- We were contacted by Business Professor Steven Rundle to analyze data from a survey. The respondents were from businesses sponsored by churches, para-church organizations, and privately run businesses in a foreign country whose purpose is to promote the gospel. The task was to answer specific questions from the data, as well as provide summary tables of the results: Business As Mission Summary Tables.
  11. Mary Frank (Summer 2012) Crime Scoring -- We were contacted by Biola Alumnus Joe Silva to develop a proprietary algorithm regarding crime. Dr. Wilson guided the research, but the project took Mary through a literature search, detailed analysis of more crime types than we’d ever want to know about, eventual creation of the algorithm, and summary into a report for the client. The plan is for the algorithm’s eventual use in web-based application. The report is not included here due to the proprietary nature of the work.
  12. Laura Evans and Courtney Turek (Fall 2011), What Do Biolans Think Of Torrey Students? A Survey -- This article describes a statistics project completed by two Research Assistants in Fall 2011. The the survey was designed by students in Dr. Wilson's Introduction to Probability Statistics class, who also collected the data by passing out surveys in selected classes at Biola University. Respondents were asked general questions about themselves as well as their opinions of Torrey students (the honors program at the University). The data was then analyzed using the statistical software R. PDF of Article: Evans and Turek (2011), What Do Biolans Think Of Torrey Students? A Survey.
  13. Kirk Spicer (Fall 2011), Analysis of Scarlet Macaw Data -- This project originated when Biola’s new Environmental Science professor, Mark McReynolds approached Dr. Wilson for statistical consultation regarding the analysis of data he had collected on Scarlet Macaws from the mountain rain forest of Beliz in 2008-09. Wanting to help, but not having adequate time to conduct the analyses himself, Dr. Wilson recruited Kirk Spicer as an RA for the project. Kirk cleaned the data (over 5000 rows and 4 columns on one of several Excel spreadsheets), loaded it into R, and condensed it into useable forms. He also conducted routine analyses and did some exploration. The entire process was guided by Dr. McReynolds original four questions, which form the basis of the report written summarizing the work. The results were used in Mr. McReynolds’ dissertation which he went on to successfully defend to earn his Ph.D in Environmental Studies.View Analysis: PDF of Article: Spicer (2011), Scarlet Macaw Data. After finishing the Scarlet Macaw project, Kirk continued RA work for Dr. Wilson in the areas of proving the asymptotic normality of the Probability of Correction Statistic, and the stages of cognitive development in geometry and other branches of math.
  14. Erin Tao and Stephanie Greer (Spring 2011), Enhancing Multiple Testing -- This project started with Erin’s request to do her Torrey Honor’s Thesis with Dr. Wilson in something related to statistics. Stephanie Greer (Spring 2011) had already worked with Dr. Wilson as an RA applying her computer science skills to obtain the neuroimaging data for the project. The process extended Dr. Wilson’s primary technical research area of the Probability of Correct Selection statistic and combined Erin’s skills with R, Matlab, and writing. The paper is currently under review with the student research journal Involve. PDF of Article: Tao and Greer (2011), Enhancing Multiple Testing.


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