Research on how students use large language model (LLM) resources, the tasks for which students use LLMs, and instructor policies and opinions surrounding LLMs has increased recently. However, there is limited research on the relationships between students’ socioeconomic backgrounds, perceptions, and usage of these resources. As finances and social status may shape students’ approach to learning, it is important to understand how these factors may influence students’ perceptions and attitudes towards emerging technologies like LLMs. Thus, we analyzed a quantitative and internally consistent student survey (N=144) and qualitative interview (N=2) responses of students taking an undergraduate-level programming course at a public university for correlations between socioeconomic background, attitudes towards LLMs, and LLM usage. Regression analysis found a significant positive association between SES and belief that LLM use will lead to career success. Qualitative interviews suggested low-SES students perceived LLMs as helpful tools for debugging and learning concepts, but not as a significant factor in long-term career success. Rather, programming knowledge itself was still paramount for career success. Our findings contribute to our understanding of the complex influences social and cultural factors have on students’ perceptions and attitudes towards LLMs.