Longitudinal Data Analysis and Time Series Commons^™

Bandwagon Behavior In Major League Baseball, Daniel E. Erro

Master's Theses

This study investigates “bandwagon” behavior among Major League Baseball (MLB) fans by analyzing Google search interest data from 2004 to 2019. Drawing on publicly available information from Google Trends, the analysis explores how fluctuations in search activity align with team performance during both the regular season and postseason. Hierarchical linear models are used to estimate expected levels of fan interest based on team performance and market characteristics. Deviations from these expectations during the regular season are interpreted as evidence of bandwagon or anti-bandwagon behavior. A drop-off in interest following playoff elimination is also examined to capture shifts in fan attention …

Policies And Price Controls On The Research And Development Of Orphan Drugs In The United States And The European Union, Bena Pearl Filipczak Smith

Master's Theses

There is substantive literature surrounding the impact of price controls on the research and development (R&D) of new pharmaceutical products. The European Union (EU) and United States (US) are often studied in contrast to examine the influence of price controls as the US has fewer pharmaceutical price controls than the EU.

We find moderate evidence that the US spent more on annual domestic pharmaceutical R&D than the EU between 2004 and 2021, on average, before and after adjusting for GDP growth per capita and year. We find strong evidence that the US increased annual domestic R&D spending at a faster …

An Empirical Evaluation Of Neural Process Meta-Learners For Financial Forecasting, Kevin G. Patel

Master's Theses

Challenges of financial forecasting, such as a dearth of independent samples and non- stationary underlying process, limit the relevance of conventional machine learning towards financial forecasting. Meta-learning approaches alleviate some of these is- sues by allowing the model to generalize across unrelated or loosely related tasks with few observations per task. The neural process family achieves this by con- ditioning forecasts based on a supplied context set at test time. Despite promise, meta-learning approaches remain underutilized in finance. To our knowledge, ours is the first application of neural processes to realized volatility (RV) forecasting and financial forecasting in general.

We …

Socioeconomic Status, Air Quality And Geographic Variation In Emergency Room Visits For Acute Bronchitis On The California Central Coast, Sean Lang-Brown, Heather W. Starnes, Gary B. Hughes

Symposium

IMPORTANCE: Analysis of geospatial variation in acute bronchitis due to socioeconomic and environmental factors can allow the efficient delivery of resources to populations most at risk.

OBJECTIVE: We sought to determine if small scale variation in socioeconomic factors and emergency room (ER) visits for acute bronchitis are associated in small cities or rural communities. We also modeled the effects of air quality on daily rates of ER visits for acute bronchitis in the context of socioeconomic factors to investigate modifying relationships.

DESIGN, SETTING, AND PARTICIPANTS: We examined ER visits for acute bronchitis in San Luis Obispo and Santa Barbara counties …

Analysis Of The Precipitation Detection Algorithm For The Geonor T-200b Precipitation Gauge To Improve Accuracy, Megan Lerman, Robert K. Goodrich

STAR Program Research Presentations

In an effort to improve the precipitation detection algorithm for the Geonor All Weather Precipitation Gauge, an automated truth algorithm has been created to detect errors in the original algorithm. The original algorithm detects precipitation in real time and uses the rate of precipitation to indicate an event. The automated truth does not detect in real time, and focuses on precipitation accumulation to indicate an event. Since the automated truth is delayed, it is able to consider the data collected before and after the point it is analyzing. The automated truth is already more accurate than the original algorithm but …

Tools And Methods To Optimize The Analysis Of Telescopic Performance Metrics On Sofia, Steven R. Wilson, Holger Jakob, Stefan Teufel, Zaheer Ali, Jeffrey Van Cleve, Brian Eney, Greg Perryman

STAR Program Research Presentations

SOFIA is an infrared observatory mounted on a modified 747 engineered to do infrared astronomy at 45000 feet. The telescope equipment contains a number of sensors and stabilizers that allow the telescope to capture images while mounted in a moving plane. We have developed methods to analyze the performance of the telescope assembly that will help improve the stabilization and image capturing performance of the observatory. Here we present reusable methods to analyze telescope performance data that will enable improvements in the quality of the scientific data that is produced by the SOFIA. This poster focuses on the multi-flight performance …

Emirical Assessment Of The Future Performance Of The S&P 500 Losers, Nicholas Powers

Statistics

In the Wall Street Journal in early 2013, there was an article posted by Andrew Bary that explored a trend in the previous 3 years of the S&P 500. The article pointed out that the average returns for the top 10 percentage decliners for 2009, 2010, and 2011 outperformed the S&P 500 for the first two weeks of the next year. These top 10 percentage decliners or losers well enough to bet on. This study looks to see if there is statistical evidence that the losers outperformed the S&P 500.

Nba Salaries: Assessing True Player Value, Michael Ghirardo

Statistics

This paper analyzes and calculates an advanced NBA statistic that is becoming more and more widely used in the NBA. The Adjusted plus-minus (APM) statistic measures a player’s contribution, independent of all other players on the court. The most appealing aspect to the APM is that it only attempts to capture how a team’s scoring margin changes with a particular player on and off the court. Scoring margin in basketball effects winning percentage greatly, so it only makes sense that players with high APM’s will increase their team’s scoring margin and, therefore, help win games. The APM statistic is not …

Is Obesity Socially Contagious?, Ciani Jean Sparks

Statistics

The main objective of this paper is to analyze three different articles that discuss whether obesity could be socially contagious. According to the World Health Organization in 2013, obesity is the fifth leading risk for deaths around the world. This disease has dramatically increased in the last decade, which has led scientists to believe there are other factors contributing to the epidemic besides genetics. The first article I analyzed, written by Nicholas Christakis and James Fowler, provided a logistic regression model to estimate the odds of a person becoming obese. The model included the explanatory variables: age, sex, education, smoking …

Analysis Of Dietary Patterns Over Freshman Year Of College, Chelsea Lofland

Statistics

This analysis is an investigation of changes in Cal Poly students’ eating habits over freshman year. The motivation behind this was an interest in college students’ lifestyles; college is the first time most students live on their own and it can be an important maturation period. College is stressful, exciting, liberating, and terrifying all at the same time. This distinctive life experience, along with my desire to handle big and messy data, led me to this research question.

The response variable analyzed was food consumption and the explanatory variables were: sex, race, quarter, food group, stress, exercise, BMI, sleep quality …

Analysis Of Roms Estimated Posterior Error Utilizing 4dvar Data Assimilation, Joseph Patrick Horton

Mathematics

The appropriateness of the approximate error calculated by the Regional Ocean Modeling System (ROMS) is analyzed using Four-Dimensional Data Assimilation (4DVAR) performed on a numerical model of the San Luis Obispo Bay. An effective method of sampling data to minimize the actual error associated with the assimilated numerical model is explored by using different data sampling methods. An idealized state of the SLO bay region ("Real Run") is created to be used as the real ocean, then a numerical model of this region is created approximating this Real Run; this is known as the "Simulated State". By taking samples from …