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Articles 1 - 8 of 8
Full-Text Articles in Statistics and Probability
Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski
Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski
Honors Scholar Theses
Challenging conventional wisdom is at the very core of baseball analytics. Using data and statistical analysis, the sets of rules by which coaches make decisions can be justified, or possibly refuted. One of those sets of rules relates to the construction of a batting order. Through data collection, data adjustment, the construction of a baseball simulator, and the use of a Monte Carlo Simulation, I have assessed thousands of possible batting orders to determine the roster-specific strategies that lead to optimal run production for the 2023 UConn baseball team. This paper details a repeatable process in which basic player statistics …
On Misuses Of The Kolmogorov–Smirnov Test For One-Sample Goodness-Of-Fit, Anthony Zeimbekakis
On Misuses Of The Kolmogorov–Smirnov Test For One-Sample Goodness-Of-Fit, Anthony Zeimbekakis
Honors Scholar Theses
The Kolmogorov–Smirnov (KS) test is one of the most popular goodness-of-fit tests for comparing a sample with a hypothesized parametric distribution. Nevertheless, it has often been misused. The standard one-sample KS test applies to independent, continuous data with a hypothesized distribution that is completely specified. It is not uncommon, however, to see in the literature that it was applied to dependent, discrete, or rounded data, with hypothesized distributions containing estimated parameters. For example, it has been "discovered" multiple times that the test is too conservative when the parameters are estimated. We demonstrate misuses of the one-sample KS test in three …
The Effects Of The Nba Covid Bubble On The Nba Playoffs: A Case Study For Home-Court Advantage, Michael Price
The Effects Of The Nba Covid Bubble On The Nba Playoffs: A Case Study For Home-Court Advantage, Michael Price
Honors Scholar Theses
The 2020 NBA playoffs were played inside of a bubble in Disney World because of the COVID-19 pandemic. This meant that there were no fans in attendance, games played on neutral courts and no traveling for teams, which in theory removes home-court advantage from the games. This setting has attracted much discussion as analysts and fans debated the possible effects it may have on the outcome of games. Home-court advantage has historically played an influential role in NBA playoff series outcomes. The 2020 playoff provided a unique opportunity to study the effects of the bubble and home-court advantage by comparing …
Exploring The Relationship Between Children’S Vocabulary And Their Understanding Of Cardinality: A Methodological Approach, Justin Slifer, Emily Carrigan, Kristin Walker, Marie Coppola
Exploring The Relationship Between Children’S Vocabulary And Their Understanding Of Cardinality: A Methodological Approach, Justin Slifer, Emily Carrigan, Kristin Walker, Marie Coppola
Honors Scholar Theses
Is there a relationship between vocabulary and children’s understanding of cardinality? Does the way in which we classify cardinality data as tested by the Give-a-Number task affect finding such a relationship? This thesis explored these questions using a methodological approach, by testing the relationship between children’s receptive vocabulary scores and Give-a-Number scores classified in two different ways, the traditional knower-level assessment, as well as by calculating the proportion of trials answered correctly. A significant correlation was found between participants’ receptive vocabulary scores and Give-a-Number scores using both manners of classification, independent of the children’s ages. The results were compared with …
Flexible Box-Cox Transformation Model For Analyzing Energy Usage At Uconn, Yutong Chen
Flexible Box-Cox Transformation Model For Analyzing Energy Usage At Uconn, Yutong Chen
Honors Scholar Theses
The Box-Cox transformation is a way to transform non-normal data into more normally distributed data. However, when we fit linear regression models to transformed data, we cannot use the Akaike Information Criterion (AIC) directly to compare different models since the transformed data are no longer on the same scale. In this study, the Jacobian adjusted AIC is proposed to compare regression models on transformed data and to select an “optimal” value of the transformation parameter. Instead of using a single for the whole data, which is commonly used in the literature and in practice, we formulate a linear regression pattern …
Analyzing Competitive Balance In Professional Sport, Kevin Alwell
Analyzing Competitive Balance In Professional Sport, Kevin Alwell
Honors Scholar Theses
In this paper we review several measures to statistically analyze competitive balance and report which leagues have a wider variance of performance amongst its competitors. Each league seeks to maintain high levels of parity, making matches and overall season more unpredictable and appealing to the general audience. Here we quantify competitive advantage across major sports leagues in numbers using several statistical methods in order for leagues to optimize their revenue.
The Psychology Of Baseball: How The Mental Game Impacts The Physical Game, Kiera Dalmass
The Psychology Of Baseball: How The Mental Game Impacts The Physical Game, Kiera Dalmass
Honors Scholar Theses
The purpose of this study was to find whether or not sports psychology can be effective. Baseball was chosen as the sport for the study because baseball can be analyzed for nearly every single factor of the game, with the exception of the mental readiness or state of the player when he steps onto the field. It therefore provides the optimal atmosphere to provide clinical and statistical support to the field of sports psychology. Despite the various, numerous pieces of literature that praise and show support for sports psychology, there hasn’t been clinical research to support it. Additionally, multiple sports …
High Frequency Data: Modeling Durations Via The Acd And Log Acd Models, Lilian Cheung
High Frequency Data: Modeling Durations Via The Acd And Log Acd Models, Lilian Cheung
Honors Scholar Theses
This thesis proposes a method of finding initial parameter estimates in the Log ACD1 model for use in recursive estimation. The recursive estimating equations method is applied to the Log ACD1 model to find recursive estimates for the unknown parameters in the model. A literature review is provided on the ACD and Log ACD models, and on the theory of estimating equations. Monte Carlo simulations indicate that the proposed method of finding initial parameter estimates is viable. The parameter estimation process is demonstrated by fitting an ACD model and a Log ACD model to a set of IBM …