Filtering by
- Creators: School of Mathematical and Statistical Sciences
- Member of: Theses and Dissertations
For our thesis, we analyzed a set of data from the on-going longitudinal study, “Aging In the Time of COVID-19” (Guest et al., ongoing) from the Center for Innovation in Healthy and Resilient Aging at Arizona State University. This study researched how COVID-19 and the resulting physical/social distancing impacted aging individuals' health, wellbeing, and quality-of-life. The survey collected data regarding over 1400 participants’ social connections, health, and experiences during COVID-19. This study gathered information about participants’ comorbid conditions, age, sex, location, etc. We presented this work in the form of a website including the traditional elements of an Honors Thesis as well as a visual essay with the data analysis portion coded with the JavaScript library D3 and a list of resources for our target audience, older adults who are experiencing social isolation and/or loneliness.
This project aims to incorporate the aspect of sentiment analysis into traditional stock analysis to enhance stock rating predictions by applying a reliance on the opinion of various stocks from the Internet. Headlines from eight major news publications and conversations from Yahoo! Finance’s “Conversations” feature were parsed through the Valence Aware Dictionary for Sentiment Reasoning (VADER) natural language processing package to determine numerical polarities which represented positivity or negativity for a given stock ticker. These generated polarities were paired with stock metrics typically observed by stock analysts as the feature set for a Logistic Regression machine learning model. The model was trained on roughly 1500 major stocks to determine a binary classification between a “Buy” or “Not Buy” rating for each stock, and the results of the model were inserted into the back-end of the Agora Web UI which emulates search engine behavior specifically for stocks found in NYSE and NASDAQ. The model reported an accuracy of 82.5% and for most major stocks, the model’s prediction correlated with stock analysts’ ratings. Given the volatility of the stock market and the propensity for hive-mind behavior in online forums, the performance of the Logistic Regression model would benefit from incorporating historical stock data and more sources of opinion to balance any subjectivity in the model.
We attempt to analyze the effect of fatigue on free throw efficiency in the National Basketball Association (NBA) using play-by-play data from regular-season, regulation-length games in the 2016-2017, 2017-2018, and 2018-2019 seasons. Using both regression and tree-based statistical methods, we analyze the relationship between minutes played total and minutes played continuously at the time of free throw attempts on players' odds of making an attempt, while controlling for prior free throw shooting ability, longer-term fatigue, and other game factors. Our results offer strong evidence that short-term activity after periods of inactivity positively affects free throw efficiency, while longer-term fatigue has no effect.
The FS in music was used in a variety of ways throughout the 20th century, primarily focusing on durations and overall structure in its use. Examples of this are found in Béla Bartók’s Music for Strings, Percussion, and Celeste (1936), Allegro barbaro (1911), Karlheinz Stockhausen’s Klavierstück IX (1955), and Luigi Nono’s il canto sospeso (1955). These works are analyzed in detail within my research, and I found every example to have a natural feel to them even if its use of the FS is carefully planned out by the composer. Bartók’s works are the least precise of my examples but perhaps the most natural ones. This imprecision in composition may be considered a more natural use of the FS in music, since nature is not always perfect either. However, in works such as Stockhausen’s, the structure is meticulously formatted in such that the precision is masked by a cycle as to appear more natural.
The conclusion of my research was a commissioned work for my instrument, the viola. I provided my research to composer Jacob Miller Smith, a DMA Music Composition student at ASU, and together we built the framework for the piece he wrote for me. We utilized the life cycle of the Black-Eyed Susan, a flower that uses the FS in its number of petals. The life cycle of a flower is in seven parts, so the piece was written to have seven separate sections in a palindrome within an overall ABA’ format. To utilize the FS, Smith used Fibonacci number durations for rests between notes, note/gesture groupings, and a mapping of 12358 as the set (01247). I worked with Smith during the process to make sure that the piece was technically suitable for my capabilities and the instrument, and I premiered the work in my defense.
The Fibonacci Series and Golden Mean in music provides a natural feel to the music it is present in, even if it is carefully planned out by the composer. More work is still to be done to develop the FS’s use in music, but the examples presented in this project lay down a framework for it to take a natural place in music composition.