Effective Resource Utilization in Arkansas Public Schools

Teacher pay in Arkansas public schools varies widely from district to district across the state. This pay discrepancy is driven by both the funds available to a district and by how these funds are allocated. There is a standard per student budget given to districts across the state, but this budget can be supplemented by additional property taxes collected on property within a district. This leaves districts with more highly valued property at an advantage. Districts are free to allocate their budget for teacher pay as they see fit, with constraints on number of students per teacher and minimum teacher salary. This research has two main objectives: 1) investigate what variables affect student performance in Arkansas public schools and 2) determine the cost-effectiveness associated with changing possible decision variables in terms of improving student performance. The objectives were achieved by using public data available through the Arkansas Department of Education. Objective 1 was accomplished using feature selection and predictive modeling. Objective 2 integrated the results found from the first objective with district budget information in order to analyze the cost-effectiveness of different district budget policies. Results from this study are valuable to districts trying to improve student performance in the most cost-effective way

Extracting Patterns in Medical Claims Data for Predicting Opioid Overdose

The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created are input to recurrent neural networks with long short-term memory cells. Hyperparameters are found through Bayesian optimization. Validation data features are reduced using weights from the best model and compared against those found using unsupervised learning techniques in other classifiers

Biases in metallicity measurements from global galaxy spectra: the effects of flux-weighting and diffuse ionized gas contamination

Galaxy metallicity scaling relations provide a powerful tool for understanding galaxy evolution, but obtaining unbiased global galaxy gas-phase oxygen abundances requires proper treatment of the various line-emitting sources within spectroscopic apertures. We present a model framework that treats galaxies as ensembles of HII and diffuse ionized gas (DIG) regions of varying metallicities. These models are based upon empirical relations between line ratios and electron temperature for HII regions, and DIG strong-line ratio relations from SDSS-IV MaNGA IFU data. Flux-weighting effects and DIG contamination can significantly affect properties inferred from global galaxy spectra, biasing metallicity estimates by more than 0.3 dex in some cases. We use observationally-motivated inputs to construct a model matched to typical local star-forming galaxies, and quantify the biases in strong-line ratios, electron temperatures, and direct-method metallicities as inferred from global galaxy spectra relative to the median values of the HII region distributions in each galaxy. We also provide a generalized set of models that can be applied to individual galaxies or galaxy samples in atypical regions of parameter space. We use these models to correct for the effects of flux-weighting and DIG contamination in the local direct-method mass-metallicity and fundamental metallicity relations, and in the mass-metallicity relation based on strong-line metallicities. Future photoionization models of galaxy line emission need to include DIG emission and represent galaxies as ensembles of emitting regions with varying metallicity, instead of as single HII regions with effective properties, in order to obtain unbiased estimates of key underlying physical properties.Comment: 37 pages, 29 figures, 4 tables. Accepted to ApJ. See Figures 15-17 for typical global galaxy biases in strong-line ratios, electron temperatures, and direct-method metallicitie

Unravelling the Dust Attenuation Scaling Relations and their Evolution

We explore the dependence of dust attenuation, as traced by the $\rm H_{\alpha}/\rm H_{\beta}$ Balmer decrement, on galactic properties by using a large sample of SDSS spectra. We use both Partial Correlation Coefficients (PCC) and Random Forest (RF) analysis to distinguish those galactic parameters that directly and primarily drive dust attenuation in galaxies, from parameters that are only indirectly correlated through secondary dependencies. We find that, once galactic inclination is controlled for, dust attenuation depends primarily on stellar mass, followed by metallicity and velocity dispersion. Once the dependence on these quantities is taken into account, there is no dependence on star formation rate. While the dependence on stellar mass and metallicity was expected based on simple analytical equations for the interstellar medium, the dependence on velocity dispersion was not predicted and we discuss possible scenarios to explain it. We identify a projection of this multi-dimensional parameters space which minimises the dispersion in terms of the Balmer decrement and which encapsulates the primary and secondary dependences of the Balmer decrement into a single parameter defined as the reduced mass $\mu = \log {\rm M}_{\star} +3.67 [{\rm O/H}] + 2.96 \log (\sigma_v/100~km~s^{-1})$. We show that the dependence of the Balmer decrement on this single parameter also holds at high redshift, suggesting that the processes regulating dust production and distribution do not change significantly through cosmic epochs at least out to z$\sim$2.Comment: 14 pages, 9 figures (+ Appendix 6 pages, 7 figures), submitted to MNRAS, comments welcom