The purpose of this study was to examine the relationship between resource allocation practices in specific categorical functions and student performance in reading and math. This study utilized quantitative research methods to study the effects of spending and performance over four years of analysis. Quantitative data was acquired utilizing information from the Texas Education Agency. The data was collected from 81 campuses and represented over 1,500 students. The study's outcomes reported that little or no correlation could be found between inputs (dollars spent in three categories) and outputs (student results in reading and math). However, subgroup analysis revealed that students from non- low socioeconomic (SES) households started out higher than their low SES counterparts, and low SES students performed worse over time in both reading and math. Math results decreased more dramatically than reading indicating a need for school-level training in data analysis to ensure that limited dollars are spent appropriately. The study recommends that principals and school administrators be especially knowledgeable in critical data analysis skills. The study further recommends that state policy-makers invest more heavily in early math instruction. In addition, the current study found that student achievement, in low-SES students, especially in mathematics is very alarming. Low SES students are starting out behind the non low-SES counterparts and perform progressively worse over time. State policy makers must address these concerns.

This thesis examined the impact of teacher quality and the socioeconomic status of students on school performance on the Texas Assessment of Knowledge and Skills Test. The data were obtained from the Academic Excellence Indicator System (AEIS) 2005-2006 Report. Disparities in education were used to examine the use of teacher quality in the No Child Left Behind Act of 2001. A multiple regression model was used and included other factors such as socioeconomic status of students, teacher salary, school funding, and student-teacher ratio. Using an ordinary least squares regression, I found that socioeconomic status of students had the most significant impact school performance. Two other variables, teacher salary and student-teacher ratio, had a significant effect on school performance suggesting alternative means of eliminating inequality in education.