Categorical Data Analysis Commons^™

Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman

Pitzer Senior Theses

This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white …

Using Neural Networks To Classify Discrete Circular Probability Distributions, Madelyn Gaumer

HMC Senior Theses

Given the rise in the application of neural networks to all sorts of interesting problems, it seems natural to apply them to statistical tests. This senior thesis studies whether neural networks built to classify discrete circular probability distributions can outperform a class of well-known statistical tests for uniformity for discrete circular data that includes the Rayleigh Test¹, the Watson Test², and the Ajne Test³. Each neural network used is relatively small with no more than 3 layers: an input layer taking in discrete data sets on a circle, a hidden layer, and an output …

Snap Scholar: The User Experience Of Engaging With Academic Research Through A Tappable Stories Medium, Ieva Burk

CMC Senior Theses

With the shift to learn and consume information through our mobile devices, most academic research is still only presented in long-form text. The Stanford Scholar Initiative has explored the segment of content creation and consumption of academic research through video. However, there has been another popular shift in presenting information from various social media platforms and media outlets in the past few years. Snapchat and Instagram have introduced the concept of tappable “Stories” that have gained popularity in the realm of content consumption.

To accelerate the growth of the creation of these research talks, I propose an alternative to video: …

State Level Earned Income Tax Credit’S Effects On Race And Age: An Effective Poverty Reduction Policy, Anthony J. Barone

CMC Senior Theses

In this paper, I analyze the effectiveness of state level Earned Income Tax Credit programs on improving of poverty levels. I conducted this analysis for the years 1991 through 2011 using a panel data model with fixed effects. The main independent variables of interest were the state and federal EITC rates, minimum wage, gross state product, population, and unemployment all by state. I determined increases to the state EITC rates provided only a slight decrease to both the overall white below-poverty population and the corresponding white childhood population under 18, while both the overall and the under-18 black population for …

How Other Drivers’ Vehicle Characteristics Influence Your Driving Speed, Russell Brockett

CMC Senior Theses

An analysis of the effect of passing vehicles’ characteristics and their impact on other drivers’ velocities was investigated.  Three experimental studies were proposed and likely outcomes were discussed.  Experiment 1 focused on the effect of passing vehicle type (SUV, sedan or truck) on driver speed.  Drivers were hypothesized as going faster when the same vehicle type as they were driving passed them versus when no vehicle or a different vehicle passed them.  Experiment 2 focused on the effect of passing SUV age on driver’s speed.  Evidence suggests passing older SUVs will increase the driver’s speed more than new SUVs.  Experiment …

Group Comparability: A Multiattribute Utility Measurement Approach To The Use Of Random Assignment With Small Numbers Of Aggregated Units, C. Anderson Johnson, John W. Graham, Brian R. Flay, William B. Hansen, Linda M. Collins

CGU Faculty Publications and Research

It is not always possible, especially in large-scale evaluation research, to ensure that random assignment will produce groups that are comparable on any number of potentially important factors. Typically, gaining comparability has been achieved only at the expense of random assignment. A method is presented that allows multivariate comparability while making only minimal restrictions on randomization. The procedure is demonstrated in the context of assigning 63 aggregated units (schools) to 28 experimental and control conditions. Good comparability of groups for all primary main effects and interactions was verified for 15 individual variables.