Cluster Analysis

Brief Description:

This course will teach you how to use various cluster analysis methods to identify possible clusters in multivariate data. Methods discussed include hierarchical clustering, k-means clustering, two-step clustering, and normal mixture models for continuous variables.

Instructor(s):
Level: Intermediate

Who Should Take This Course:

• Marketing analysts who need to cluster customer data as part of a market segmentation strategy;
• Computational biologists (e.g. for taxonomy);
• Environmental scientists (e.g. for habitat studies);
• IT specialists (e.g. in modeling web traffic patterns);
• Military and national security analysts (e.g. in automated analysis of intercepted communications).

Dates:
November 02, 2012 to November 30, 2012November 01, 2013 to November 29, 2013
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

Register Online -$499
Register Online -$399 (you must be affiliated with a college, university or high school)

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise. Multiple course registrations may be entitled to tuition discounts; read more.

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Cluster Analysis

Aim of Course:

This course will teach you how to use various cluster analysis methods to identify possible clusters in multivariate data. In marketing applications, clusters of customer records are called market segments (and the process is called market segmentation). Methods discussed include:

• hierarchical clustering (in which smaller clusters are nested inside larger clusters);
• k-means clustering;
• two-step clustering;
• normal mixture models for continuous variables.

This course is a core requirement or elective in the following Program(s) in Advanced Statistical Studies (PASS):

• Biostatistics (Epidemiology)

• Business Analytics

• Data Mining

• Statistics for Environmental Science

Prerequisite(s):

Some familiarity with multivariate data is also helpful, such as that provided in Introduction to Data Mining (though the methods discussed in that course are not required for this course).

Course Program:

SESSION 1: Hierarchical clustering

• Hierarchical clustering - dendrograms
• Divisive vs. agglomerative methods
• Different linkage methods

SESSION 2: K-means clustering

SESSION 3: Normal mixture model

• Finite mixture model
• K-means cluster as a special case

SESSION 4: Other approaches

• SPSS two-step
• COSA - Clustering Objects on Subsets of Attributes (runs under R)

Organization of the Course:

This course takes place over the internet, at statistics.com for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and you will receive individual feedback on your homework answers.

Credit:
Students come to The Institute for a variety of reasons:

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Program in Advanced Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).

As you begin the class, you will be asked to specify your category.

This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a record of course completion will be issued by Statistics.com, upon request.

Course Text:

The required text is Cluster Analysis, 5th Edition, by Brian S. Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl, published by Wiley. You can order the text from the publisher by clicking here.  Wiley typically offers statistics.com customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount -- try calling your regional Wiley representative.)

Software:

Some illustrations will be provided using XLMiner (an Excel add-in) and SPSS.   Instructor is familiar with both, but TA will be able to provide assistance only with XLMiner. Click Here for information on obtaining a free (or nominal cost) copy of XLMiner and SPSS.

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Yes, I want to register for:

Cluster Analysis

Instructor(s):
Dates:
November 02, 2012 to November 30, 2012November 01, 2013 to November 29, 2013
Course Fee: $499
Academic Discounted Rate: $399

Before registering, please read the syllabus tab, noting the prerequisites, text and software requirements. When you click the register button, you will be taken to our secure transaction page.

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