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What is it and how does it work?

Statistical Reasoning is an introductory statistics course offered through the Open Learning Initiative (OLI). It is designed to teach the basic concepts of statistics and the logic of statistical reasoning. The only prerequisite is basic algebra. Although students work through the course independently, it includes many interactive elements including simulations, “walk-throughs” that integrate voice and graphics to explain an example of a procedure or a difficult concept, and, most prominently, computer tutors in which students practice problem solving, with hints and immediate feedback.

NOTE: The probability unit of the Statistical Reasoning course functions as a “bridge” to the inference section and includes only those concepts necessary to support a conceptual understanding of the role of probability as the “machinery” behind inference. For educators who are looking for a resource that addresses probability in greater depth, please see the Probability and Statistics OLI course.

Which skill(s) are targeted?

• Identify, define, and navigate the data and information landscape 
• Critically evaluate data and information 
• Analyze data  and engage with information in and across communities of practice

Who else has used it?

• Ò»±¾µÀÎÞÂë’s Statistics and Data Science instructors have used this online course as an interactive textbook (instead of a traditional textbook) and homework resource for various introductory statistics courses in their undergraduate curriculum.
• Ò»±¾µÀÎÞÂë’s Human-Computer Interaction Institute and Psychology Department have assigned this online course as a pre-matriculation activity for some of their programs’ graduate students to complete before beginning their program of study – i.e., as a “bridge” course that helps students enter the program with foundational statistics knowledge and skills.
• Various Ò»±¾µÀÎÞÂë instructors have made this online course available to students in their intermediate-level undergraduate statistics and research methods courses as a supplemental resource – e.g., for students who want to independently review foundational statistics knowledge and skills they will need to apply as they learn new material.