Decoherence and definite outcomes

This thesis has three aims: (1) to clarify in detail the relation between the decoherence mechanism and the problem of definite outcomes, (2) to dispel common misconceptions about the measurement problem in quantum mechanics, and (3) to present some recent alternative approaches in the quest for a satisfactory solution of the definite outcomes problem.Comment: 102 pages, in English. Thesis work for the "Laura Magistrale Interfacolt\`a in Logica, Filosofia e Storia della Scienza" at Universit\`a degli studi di Firenze. Supervisors: Prof. Roberto Casalbuoni and Prof. Elena Castellan

Fair Inference On Outcomes

In this paper, we consider the problem of fair statistical inference involving outcome variables. Examples include classification and regression problems, and estimating treatment effects in randomized trials or observational data. The issue of fairness arises in such problems where some covariates or treatments are "sensitive," in the sense of having potential of creating discrimination. In this paper, we argue that the presence of discrimination can be formalized in a sensible way as the presence of an effect of a sensitive covariate on the outcome along certain causal pathways, a view which generalizes (Pearl, 2009). A fair outcome model can then be learned by solving a constrained optimization problem. We discuss a number of complications that arise in classical statistical inference due to this view and provide workarounds based on recent work in causal and semi-parametric inference

Effective Student Outcomes Assessment Plan Reform Strong Undergraduate Curriculum Plan

The undergraduate curriculum committee from the Bob L. Herd Department of Petroleum Engineering at Texas Tech University has made significant modifications that were determined by a systematic student outcomes assessment plan. This paper shows how the department assessment plan facilitated continuous actions of improvement and ultimately provides an example of how a strong undergraduate curriculum plan was constructed. The paper highlights the details of the department assessment plan, such as how ABET student outcomes are mapped to department undergraduate courses, what assessment tools were used, when data were gathered and evaluated, and how the analysis of data was utilized to implement actions of improvement. Finally, the paper provides two examples of significant actions of improvement, made based on the department assessment and evaluation plan.Cockrell School of Engineerin

Treatment Effects on Ordinal Outcomes: Causal Estimands and Sharp Bounds

Assessing the causal effects of interventions on ordinal outcomes is an important objective of many educational and behavioral studies. Under the potential outcomes framework, we can define causal effects as comparisons between the potential outcomes under treatment and control. However, unfortunately, the average causal effect, often the parameter of interest, is difficult to interpret for ordinal outcomes. To address this challenge, we propose to use two causal parameters, which are defined as the probabilities that the treatment is beneficial and strictly beneficial for the experimental units. However, although well-defined for any outcomes and of particular interest for ordinal outcomes, the two aforementioned parameters depend on the association between the potential outcomes, and are therefore not identifiable from the observed data without additional assumptions. Echoing recent advances in the econometrics and biostatistics literature, we present the sharp bounds of the aforementioned causal parameters for ordinal outcomes, under fixed marginal distributions of the potential outcomes. Because the causal estimands and their corresponding sharp bounds are based on the potential outcomes themselves, the proposed framework can be flexibly incorporated into any chosen models of the potential outcomes, and are directly applicable to randomized experiments, unconfounded observational studies, and randomized experiments with noncompliance. We illustrate our methodology via numerical examples and three real-life applications related to educational and behavioral research.Comment: Accepted by the Journal of Education and Behavioral Statistic