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In science classrooms, scientific knowledge is often portrayed as certain, yet uncertainty is inherent to scientific practice. Scientific uncertainty deserves special attention, as it has increasingly become part of public discussion and is susceptible to manipulation. This paper presents an argument for teaching about scientific uncertainty, and describes an empirical study that led to a typology of scientific uncertainty that holds promise for science teaching. The four types of uncertainty described in this paper are two types of uncertainty in data, and two types of uncertainty in models. Each of these have pedagogical implications for teaching science, and can spark critical discussions about data and models that scientists use to justify claims about the natural world.