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

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Course name
STAT495-Advanced-Data-Analysis
Institution
Amherst College
Instructor
Nicholas Horton
Wikipedia Expert
Ian (Wiki Ed)
Subject
Statistics
Course dates
2016-09-06 00:00:00 UTC – 2016-12-22 23:59:59 UTC
Approximate number of student editors
12


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.

Student Assigned Reviewing
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 Conditional probability
Mowen17 Complex Normal Distribution Complex Normal Distribution
Cki17 Imputation (statistics) Imputation (statistics)
Oliviaxu17 Look-elsewhere effect Look-elsewhere effect
Llee17 Bayes factor
Wuthering313 Maui High School
Akim17 La Canada Flintridge, Survival Analysis La Canada Flintridge, California, Survival analysis
Ajav13 Digital marketing, Machine Learning
Sfloresramos17 Predictive probability of success Predictive probability of success

Timeline


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