Critical reading skills are essential for understanding data stories and solving problems in statistics courses, and they are ultimately necessary for interpreting research articles and communicating with other professionals in a data-driven world. Educators can use various methods to help students to develop the critical reading skills needed for being successful in quantitative work. As expert readers in their field, statistics instructors can demonstrate how to read quantitative content through metacognitive and modeling approaches. This paper will present information about documented quantitative reading struggles and examples of helpful instructional strategies such as thinking aloud, annotating, and using visuals. Such strategies can provide students with tools that assist them in dealing with potential barriers to effective reading, such as complex notation and lexical ambiguity. Examples of assignments that promote critical reading skills in statistics courses will be shared.