This course will teach you the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors.
This course will teach you the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors.
Statistics deals with collections of data organized in 1,2,3 or more dimensions. Matrix notation is the best way to compactly represent such data. This course provides the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods including the matrix inverse, generalized inverse and eigenvalues and eigenvectors.
Students who complete this course will be introduced to vectors and matrices, matrix inverse and linear equations, Eigenvalues and Eigenvectors, and symmetric matrices. It is designed to be a refresher, or an introduction to matrix methods for anyone interested in multivariate statistics, modeling, designing experiments or data mining.
Matrix algebra is used heavily in multivariate statistics, and the theory behind many statistical modeling procedures. Matrix notation is used even more widely. If you are interested in taking courses in multivariate statistics, modeling, design of experiments, data mining or other topics involving multivariate data and need a refresher in, or introduction to matrix methods, you should take this course.
Dr. Robert LaBudde is president and founder of Least Cost Formulations, Ltd., a mathematical software development company specializing in optimization and process control software for manufacturing companies. He has served on the faculties of the University of Wisconsin, Massachusetts Institute of Technology, Old Dominion University and North Carolina State University. Dr. LaBudde is currently Adjunct Professor of Statistics at Old Dominion University.
Introduction to Vectors and Matrices
Matrix Inverse & linear Equations
Eigenvalues and Eigenvectors
Symmetric matrices
Mar 24, 2023 to Apr 21, 2023
Aug 11, 2023 to Sep 8, 2023
No classes scheduled at this time.
No classes scheduled at this time.
You should be familiar with intermediate or college algebra, including solving systems of linear equations.
We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.
The additional preparation found in Introduction to Statistics 3 – Regression and ANOVA is also helpful.
The instructor, Dr. LaBudde was highly effective. His written lectures contributed greatly to my understanding and his patient and lengthy answers to my at times overly general questions were extremely informative. It would be hard or impossible to get this information on my own
This course takes place online at The Institute 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.
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 at the end of the week, you will receive individual feedback on your homework answers.
This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.
Homework in this course consists of guided numerical problems to test the concepts.
In addition to assigned readings, this course also has the instructor’s expert write-ups on important concepts.
All course materials will be provided in the course.
For those who wish additional resources, a recommended text is Matrix Algebra: An Introduction by Krishnan Namboodiri from Sage. Sage Publication offers discounts to students at Statistics.com for many of their titles when the code S06SC is used during checkout on their website (the “0” is a zero not an alphabetical “O”). If you are located in Asia, the web procedure for your location may not accept this discount, try calling your regional Sage representative.
There is no requirement for software in this course. All of the assignments can be done by hand. However, the text illustrates some examples using SAS and the course notes using Microsoft Excel and R.
Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?”
Enrollment
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.
Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.
Group Rates
Contact us to get information on group rates.
Discounts
Academic affiliation? In most courses you are eligible for a discount at checkout. Use promo code ACADEMIC where prompted during registration.
Invoice or Purchase Order
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.
This course is eligible for the following credit and recognition options:
No Credit
You may take this course without pursuing credit or a record of completion.
Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.
CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.
INFORMS-CAP
This course is recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam and can help CAP® analysts accrue Professional Development Units to maintain their certification.
ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the lower-division baccalaureate/associate degree, 3 semester hours in mathematics. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.
There is no supplemental content for this course.
There is no additional information for this course.
