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This course includes self-guiding materials and activities, and is ideal for independent learners, or instructors trying out this course package.
OLI does not provide any verification of completion. If you would like to receive credits for completing this course, please make arrangements with your local institution.
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Introduces the basic concepts, logic, and issues involved in statistical reasoning. Topics include Exploratory Data Analysis, Producing Data and Study Design, Probability and Statistical Inference.
Select a course version below to choose the format in which you want to do the activities. You will need your own copy of Microsoft Excel, Minitab, or R software to do the activities.
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Measuring the Effectiveness of the OLI Statistics Course in Accelerating Student Learning
Course includes all expository text, simulations, case studies, comprehension tests, interactive learning exercises and the StatTutor labs (cognitive tutors).
This online course is comparable to the full semester course on Statistics taught at Carnegie Mellon University. Your access includes the complete online course including all expository text, simulations, case studies, comprehension tests, interactive learning exercises and StatTutor. The course covers the topics of Exploratory Data Analysis, Producing Data and Study Design, Probability and Statistical Inference. The full course is available in three versions. Each version uses a different statistical package.
The Open & Free Statistics course does NOT include access to the end-of-module graded exams or to the course instructor. No credit is awarded for completing the Open & Free Statistics course.
Academic versions of this course are available in the three available packages: Minitab, Excel, and R. They are offered through educational institutions which award accreditation. Students taking an Academic Course have access to the same course materials as the students taking the Open & Free Course PLUS access to graded exams. The Academic courses track student's learning of key concepts and give the student and the instructor formative feedback to improve learning outcomes.
This course introduces students to the basic concepts, logic, and issues involved in statistical reasoning. Major topics include exploratory data analysis, an introduction to research methods, probability, and statistical inference. The objectives of this course are to give students confidence in manipulating and drawing conclusions from data and provide them with a critical framework for evaluating study designs and results.
An important feature of the course is the use of an intelligent tutoring system developed at Carnegie Mellon called "StatTutor." StatTutor aims to facilitate understanding of statistical ideas and analytical techniques by helping students construct useful knowledge representations and thereby develop effective problem-solving skills. It uses a specified outline of steps to follow in solving problems, or "scaffolding". StatTutor will use scaffolding and immediate feedback flexibly, tracking and responding to individual students as they navigate the learning environment.