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For my Statistics class, I am building a module that can easily explain certain statistical methods to students, and get the required results. For this, I am developing a list of the most important statistical methods, so I can implement them in my module.

Obviously linear regression, correlations, significance tests will be implemented, but what would your preference be?

My audience will range from students starting with statistics to our 'advanced' students. So please feel free to name unconventional methods. My students will be majoring / mastering in Sociology, Politicology and other social sciences.

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Shouldn't you specify who your audience is? – ocram Jan 24 at 11:23
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Welcome to the site. Why not look at the syllabus of your course or some other similar course? Your list of three seems a little odd, as "significance tests" isn't the same sort of thing as "regression" and "correlation". If you want more specific answers, I think we'd have to know who your students are, what their backgrounds are, and so on. I'm also curious what this "module" will be. There is surely no shortage of books, web application, web pages and so on explaining basic statistics. – Peter Flom Jan 24 at 11:25
Thanks for your comments. Think of it as an interactive platform for statistics. Still figuring out the specifics, but in order to think of those, I need to be quite sure I don't miss any important methods. – Mats Willemsen Jan 24 at 11:28

closed as not constructive by Andy W, Macro, cardinal, whuber♦ Jan 24 at 18:34

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I liked the course offered at coursera: https://www.coursera.org/course/stats1

Your course might be longer and so you may need put more stuff in the course syllabus.

A good introductory stats course should cover the following topics: Intro to proabability and distributions sampling, bootstrap methods descriptive stats correlation linear regression, maybe some intro to nonlinear regression (depending of interest of your class) confidence intervals t-test, chi-square test anova and manova

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