Course Course Summary Section 1 Content Section 1 Content Left Section 1 Content Right Credit Type: Course ACE ID: STAT-0020 Organization: Statistics.com Location: Classroom-based Length: 4 weeks (60 hours) Dates Offered: 3/1/2018 - 6/30/2021 12/1/2014 - 2/28/2018 Credit Recommendation & Competencies Section 2 Content Section 2 Content Left Section 2 Content Right Level Credits (SH) Subject Upper-Division Baccalaureate 3 Statistics or Data Mining Description Section 3 Content Section 3 Content Left Section 3 Content Right Objective: The course objective is to cover statistical methods to identify possible clusters in multivariate data, including hierarchical clustering, k-means clustering, two-step clustering and normal mixture models. Learning Outcomes: Apply mixture models to multivariate data and interpret the output Interpret and diagnose the output of different clustering procedures. Conduct hierarchical cluster analysis and k-means clustering to identify clusters in multivariate data Apply normalization of data appropriately in cluster analysis Identify the assignment of cases to clusters General Topics: Hierarchical clustering (in which smaller clusters are nested inside larger clusters) K-means clustering Two-step clustering Normal mixture models for continuous variables Instruction & Assessment Section 4 Content Section 4 Content Left Section 4 Content Right Instructional Strategies: Case Studies Classroom Exercise Computer Based Training Discussion Lectures Practical Exercises Methods of Assessment: Case Studies Quizzes Minimum Passing Score: 70% Supplemental Materials Section 5 Content Section 5 Content Left Section 5 Content Right Section 6 Content Section 6 Content Left Section 6 Content Right Button Content Rail Content 1 Other offerings from Statistics.com Biostatistics for Credit (STAT-0002) Calculus Review (STAT-0038) Categorical Data Analysis (STAT-0006) Customer Analytics in R (STAT-0031) Customer Analytics in R with Capstone (STAT-0053) Forecasting Analytics (STAT-0021) Forecasting Analytics with Capstone (STAT-0051) Integer & Nonlinear Programming and Network Flow (STAT-0019) Integer & Nonlinear Programming and Network Flow with Capstone (STAT-0050) Interactive Data Visualization (STAT-0028) View All Courses Page Content