Boxplots and Tables OpenCourseWare: A Free Bachelor Level Class on Boxplots and Tables by The Open University

Published Feb 12, 2009

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'Interpreting Data: Boxplots and Tables,' a free course that is provide by The Open University, examines boxplots and tables that are commonly used to display one or more data sets in visual form for the purpose of analyzing data, performing calculations or creating graphs. Students who are pursuing degree programs, such as the Bachelor of Science in Mathematics, will benefit from the intermediate-level information that is contained in this course.

Interpreting Data: Boxplots and Tables: Course Specifics

Degree Level Free Audio Video Downloads
Undergraduate Yes No No Yes

Lectures/Notes Study Materials Tests/Quizzes
Yes Yes No

Interpreting Data: Boxplots and Tables: Course Description

'Interpreting Data: Boxplots and Tables' focuses on the mathematical techniques that utilize tools like boxplots and tables to present numerical information in a visual format. These tools not only make it easier to display data or a set of objects, but they also provide visual assistance when performing comparisons and calculations. This OpenCourseWare is provided by The Open University's Mathematics and Statistics Department. This free course covers a wide range of topics, including simple boxplots, comparing data sets, data sets in different tabular forms, basic table layouts and several useful calculations. Case studies expose students to multiple applications of boxplots and tables in different scenarios, including a look at early retirement data from the National Health Service, the British Crime Survey and HIV testing in sub-Saharan Africa. Students will also gain the practical knowledge and skills necessary for graphically displaying data objects in boxplot and tabular form, explaining and evaluating data, presenting data objects in tables to clarify patterns and making decisions on the best type of graphs for displaying tabular data.

Materials for this course include online unit notes, discussion forums, a knowledge map and a bibliographic list of recommended readings. If you would like to take advantage of this course, visit the boxplot and tables course page.

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