Wikipedia:Wiki Ed/Amherst College/STAT495-Advanced-Data-Analysis (Fall2016)
{{course details
| course_name = STAT495-Advanced-Data-Analysis
| instructor_username = Bikestats
| instructor_realname = Nicholas Horton
| support_staff = Ian (Wiki Ed)
| subject = Statistics
| start_date = 2016-09-06 00:00:00 UTC
| end_date = 2016-12-22 23:59:59 UTC
| institution = Amherst College
| expected_students = 12
| assignment_page = Wikipedia:Wiki_Ed/Amherst_College/STAT495-Advanced-Data-Analysis_(Fall2016)
| dashboard.wikiedu.org = yes
}}
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 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.
{{students table}}
{{student table row|Jbrowning17|Pioneer Valley Transit Authority, Multiple comparisons problem|Multiple comparisons problem}}
{{student table row|Trant22t|Logistic regression|Logistic regression}}
{{student table row|Cokusiak|Johnny Appleseed, Statistical significance|Johnny Appleseed, Statistical significance}}
{{student table row|Chaley17|Stochastic process|Stochastic process}}
{{student table row|MulingS|Amherst College, Conditional probability|Conditional probability}}
{{student table row|Mowen17|Complex Normal Distribution|Complex Normal Distribution}}
{{student table row|Cki17|Imputation (statistics)|Imputation (statistics)}}
{{student table row|Oliviaxu17|Look-elsewhere effect|Look-elsewhere effect}}
{{student table row|Llee17|Bayes factor|}}
{{student table row|Wuthering313|Maui High School|}}
{{student table row|Akim17|La Canada Flintridge, Survival Analysis|La Canada Flintridge, California, Survival analysis}}
{{student table row|Ajav13|Digital marketing, Machine Learning|}}
{{student table row|Sfloresramos17|Predictive probability of success|Predictive probability of success}}
{{end of students table}}
{{start of course timeline}}
= Week 1 =
{{start of course week|2016-09-14|2016-09-16}}
{{in class|In class - Introduction to the Wikipedia project}}
Welcome to your Wikipedia project's course timeline. This page will guide you through the Wikipedia project for your course. Be sure to check with your instructor to see if there are other pages you should be following as well.
Your course has also been assigned a Wikipedia Content Expert. Check your Talk page for notes from them. You can also reach them through the "Get Help" button on this page.
To get started, please review the following handouts:
- [http://wikiedu.org/editingwikipedia Editing Wikipedia] pages 1–5
- [http://wikiedu.org/evaluatingwikipedia Evaluating Wikipedia]
{{assignment|Assignment - Practicing the basics}}
- Create an account and join this course page, using the enrollment link your instructor sent you.
- It's time to dive into Wikipedia. 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 grade.
- When you finish the trainings, practice by introducing yourself to a classmate on that classmate’s Talk page.
{{end of course week}}
= Week 2 =
{{start of course week|2016-09-19|2016-09-21}}
{{assignment|Assignment - Critique an article}}
It's time to think critically about Wikipedia articles. You'll evaluate a Wikipedia article, and leave suggestions for improving it on the article's Talk page.
- Complete the "Evaluating Articles and Sources" training (linked below).
- Choose an article, and consider some questions (but don't feel limited to these):
- Is each fact referenced with an appropriate, reliable reference?
- Is everything in the article relevant to the article topic? Is there anything that distracted you?
- Is the article neutral? Are there any claims, or frames, that appear heavily biased toward a particular position?
- Where does the information come from? Are these neutral sources? If biased, is that bias noted?
- Are there viewpoints that are overrepresented, or underrepresented?
- Check a few citations. Do the links work? Is there any close paraphrasing or plagiarism in the article?
- Is any information out of date? Is anything missing that could be added?
- 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 — Bikestats (talk) 12:38, 24 October 2016 (UTC).
{{end of course week}}
= Week 3 =
{{start of course week|2016-09-26|2016-09-28|2016-09-30}}
{{assignment|Assignment - Add to an article}}
Familiarize yourself with editing Wikipedia by adding a citation to an article. There are two ways you can do this:
- Add 1-2 sentences to a course-related article, and cite that statement to a reliable source, as you learned in the online training.
- The [https://tools.wmflabs.org/citationhunt/en?id=001996f6&cat=all Citation Hunt] 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 statement.
{{end of course week}}
= Week 4 =
{{start of course week|2016-10-03|2016-10-05|2016-10-07}}
{{assignment|Assignment - Copyedit an article (redux)}}
- 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 can).
- 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 "Wikipedia-summary.pdf"
{{end of course week}}
= Week 5 =
{{start of course week|2016-10-14}}
{{end of course week}}
= Week 6 =
{{start of course week|2016-10-17|2016-10-19|2016-10-21}}
{{end of course week}}
= Week 7 =
{{start of course week|2016-10-24|2016-10-26|2016-10-28}}
{{end of course week}}
= Week 8 =
{{start of course week|2016-10-31|2016-11-02|2016-11-04}}
{{end of course week}}
= Week 9 =
{{start of course week|2016-11-07|2016-11-09|2016-11-11}}
{{end of course week}}
= Week 10 =
{{start of course week|2016-11-14|2016-11-16|2016-11-18}}
{{end of course week}}