Principal Components and Factor Analysis

Brief Description:

In this course, you will learn how to make decisions in building a factor analysis model - including what model to use, the number of factors to retain, and the rotation method to use.

Instructor(s):
Level: Intermediate/advanced

Who Should Take This Course:

Market researchers, educational and psychological researchers, sociologists, political scientists, survey researchers.

Dates:
May 25, 2012 to June 22, 2012May 24, 2013 to June 21, 2013
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

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

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Principal Components and Factor Analysis

Aim of Course:

Exploratory factor analysis (EFA) is a method of identifying the number and nature of latent variables that explain the variation and covariation in a set of measured variables. In this course, you will learn how to make decisions in building an EFA model - including what model to use, the number of factors to retain, and the rotation method to use. Because of similarities in the underlying mathematics, factor analysis routines often offer principal components analysis (PCA) as a method of "factoring", yet EFA and PCA have different models and serve different goals. This course covers the theory of EFA and PCA, and features practical work with computer software and data examples. At the conclusion of the course students will understand the differences between EFA and PCA and will be able to specify different forms of factor extraction and rotation.

Prerequisite(s):

Some prior work with modeling is also helpful - statistics.com courses that are useful in this respect include Regression, Introduction to Data Mining, and Logistic Regression.

Course Program:

SESSION 1: Methods

• Principal Components Analysis
• Principal Axes Factor Analysis
• Maximum Likelihood Factor Analysis

SESSION 2: Choosing the correct number of factors

• Scree plot
• Parallel analysis
• Retaining factors with ML factor analysis

SESSION 3: Rotation

• Varimax
• Quartimax
• Oblique rotation

SESSION 4: Use of factor scores

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 text is Foundations of Factor Analysis by Stanley A. Mulaik, published by CRC Press, Taylor and Francis. To order it directly from the publisher, please click here. To receive a special price from the publisher, fill out this form and fax or email it back to them.

Software:

The course will provide illustrations in IBM SPSS Statistics 18 (formerly known as PASW Statistics 18 and also as SPSS). Students are welcome to use other suitable software, although IBM SPSS Statistics GradPac 18 is recommended. The instructor will not be able to provide individualized software instructional support for software other than IBM SPSS Statistics. Click here for software options.

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Principal Components and Factor Analysis

Instructor(s):
Dates:
May 25, 2012 to June 22, 2012May 24, 2013 to June 21, 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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