Knowledge

:Wiki Ed/Amherst College/STAT495-Advanced-Data-Analysis (Fall2016) - Knowledge

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interpretation of complex and real-world datasets that go beyond textbook problems. Course topics will vary from year to year depending on the instructor and selected case studies. Topics may include visualization techniques to summarize and display high dimensional data, advanced topics in design and linear regression, selected topics in data mining, nonparametric analysis, and analysis of network data. Through a series of case studies, students develop the capacity to think and compute with data, undertake and assess analyses, and effectively communicate their results using written and oral presentation.
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Our world is awash in data. To allow decisions to be made based on evidence, there is a need for statisticians to be able to make sense of the data around us and communicate their findings. In this course, students will be exposed to advanced statistical methods and will undertake the analysis and
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tool shows unreferenced statements from articles. First, evaluate whether the statement in question is true! An uncited statement could just be lacking a reference or it could be inaccurate or misleading. Reliable sources on the subject will help you choose whether to add it or correct the
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It's time to dive into Knowledge. Below, you'll find the first set of online trainings you'll need to take. New modules will appear on this timeline as you get to new milestones. Be sure to check back and complete them! Incomplete trainings will be reflected in your
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Using your chosen statistical article. Read through it, thinking about ways to improve the language, such as fixing grammatical mistakes. Then, make the appropriate changes. You don’t need to contribute new information to the article (but you
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Welcome to your Knowledge project's course timeline. This page will guide you through the Knowledge project for your course. Be sure to check with your instructor to see if there are other pages you should be following as
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This course page is an automatically-updated version of the main course page at dashboard.wikiedu.org. Please do not edit this page directly; any changes will be overwritten the next time the main course page gets
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Please submit a brief (1 page) summary and overview of your changes along with a reflection on the process  (no more than 2 pages double spaced) by the end of the day on Monday to your private github repo as
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Choose at least 2 questions relevant to the article you're evaluating. Leave your evaluation on the article's Talk page. Be sure to sign your feedback with four tildes —
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It's time to think critically about Knowledge articles. You'll evaluate a Knowledge article, and leave suggestions for improving it on the article's Talk page.
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Your course has also been assigned a Knowledge Content Expert. Check your Talk page for notes from them. You can also reach them through the "
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Add 1-2 sentences to a course-related article, and cite that statement to a reliable source, as you learned in the online training.
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Familiarize yourself with editing Knowledge by adding a citation to an article. There are two ways you can do this:
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Is the article neutral? Are there any claims, or frames, that appear heavily biased toward a particular position?
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When you finish the trainings, practice by introducing yourself to a classmate on that classmate’s Talk page.
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Check a few citations. Do the links work? Is there any close paraphrasing or plagiarism in the article?
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Is everything in the article relevant to the article topic? Is there anything that distracted you?
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Create an account and join this course page, using the enrollment link your instructor sent you.
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Where does the information come from? Are these neutral sources? If biased, is that bias noted?
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Choose an article, and consider some questions (but don't feel limited to these):
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Is any information out of date? Is anything missing that could be added?
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Complete the "Evaluating Articles and Sources" training (linked below).
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Are there viewpoints that are overrepresented, or underrepresented?
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Is each fact referenced with an appropriate, reliable reference?
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To get started, please review the following handouts:
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Index

Knowledge:Wiki Ed
Dashboard
Discussion
Activity Feed
Edit this page
Interactive training
Editing guidelines (PDF)
Help pages (PDF)
More resources
Other courses
Nicholas Horton
Ian (Wiki Ed)
Jbrowning17
Pioneer Valley Transit Authority
Multiple comparisons problem
Multiple comparisons problem
Trant22t
Logistic regression
Logistic regression
Cokusiak
Johnny Appleseed
Statistical significance
Johnny Appleseed
Statistical significance
Chaley17
Stochastic process
Stochastic process
MulingS
Amherst College
Conditional probability

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