This tutorial connects perspectives from psychology and natural-language processing to study cognitive effects and biases in large language models. It examines how concepts developed for human cognition are transferred to LLM evaluation, clarifies differences in assumptions and methodology across disciplines, and discusses challenges in designing valid experiments. The tutorial also surveys practical evaluation strategies and open research questions, with the goal of helping researchers distinguish superficial behavioral similarities from stronger claims about human-like cognition or bias in language models.