Although sampling techniques have been used effectively in education research and practice it is not clear how stratified random sampling techniques apply to high-stakes testing in the current educational environment. The present study focused on representative sampling as a possible means for reducing the quantity of state-administered tests in Texas public education. The purpose of this study was two-fold: (1) to determine if stratified random sampling is a viable option for reducing the number of students participating in Texas state assessments, and (2) to determine which sampling rate provides consistent estimates of the actual test results among the population of students. The study examined students’ scaled scores, percent of students passing, and student growth over a three-year period on state-mandated assessments in reading, mathematics, science, and social studies. Four sampling rates were considered (10%, 15%, 20%, & 25%) when analyzing student performance across demographic variables, including population estimates by socioeconomic status, limited English proficiency, and placement in special education classes. The data set for this study included five school districts and 68,641 students. Factorial ANOVAs were used initially to examine the effects of sampling rate on bias in reading and mathematics scores and bias in percentage of students passing these …