Online Course in the Introduction to Linear Models and Matrix Algebra

edX offers an online course "Introduction to Linear Models and Matrix Algebra". Matrix algebra forms the basis of many current tools for experimental design and high-dimensional data analysis. This course will use matrix algebra to represent the linear models commonly used to model differences between experimental units and will perform statistical inference on these differences. The course will use the R programming language to perform array operations. This series has been divided into seven parts to suit different educational levels of learners. You can take this whole series or the individual courses that interest you since if you are a statistician you can skip the first two or three courses, similarly if you are a biologist you can skip some introductory biology lectures. You will need knowledge of some basic statistics for this course, and by the third cycle, advanced statistical concepts such as hierarchical models, and advanced software engineerings skills, such as parallel computing and iterable search concepts, will be taught.
You will learn both of the following through this course:

• Notes on Matrix Algebra.
• Matrix algebra operations.
• Apply matrix algebra to data analysis.
• linear models
• A brief introduction to QR analysis.

Benefits:

• You will get this course in just 4 weeks for 2-4 hours per week.
• In this course, you will learn at your own pace.
• You will get this course for free.
• You can enroll in the Verified track for $149 USD, and you will get a certificate that you can share upon completion of the course, and it will also give you access to assignments and exams.

To apply for this opportunity, click here,  then register on the website with the required information.

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