Statistical and Machine Learning Methods for Analyzing Clusters and Detecting Anomalies (613)(v.1)
  • Type Validation
  • Level Advanced
  • Time Weeks
Additional Details

Statistical and Machine Learning Methods for Analyzing Clusters and Detecting Anomalies (613)(v.1)

Issued by Statistics.com

The course objective is to teach how to use machine learning and statistical methods to identify clusters in multivariate data, i.e., groups of cases that have relatively high within-group similarity. Using those same methods, and additional ones, students will also learn how to identify cases that are relatively unique - anomalies (also called outliers).

  • Type Validation
  • Level Advanced
  • Time Weeks
Additional Details

Skills

Earning Criteria

  • The methods of assessment include quizzes, with a minimum passing score of 80%.
  • Instructional strategies include: discussion, computer-based training, practical exercises.

Endorsements

  • American Council on Education

    American Council on Education

    This credential has been successfully evaluated by the American Council on Education for college credit. It is recommended for a total of 3 Graduate college credits in Statistics. For more information about ACE Learning Evaluations, visit www.acenet.edu.
  • American Council on Education

    American Council on Education

    3 semester hours in statistics in the graduate category