The data whose dimension is larger than dimensions considered in the classical multivariate analysis is studied in the field of High-Dimensional Statistics relying on the theory of random vectors. This [course_title] helps you solve the problems related to various proof techniques for state-of-the-art methods in regression, matrix estimation, and principal component analysis and optimally guarantees more effectively.
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.
Having an Official Edukite Certification is a great way to celebrate and share your success. You can:
- Add the certificate to your CV or resume and brighten up your career
- Show it to prove your success
Course Credit: MIT
|Introduction to High-Dimensional Statistics||00:15:00|
|Linear Regression Model||00:25:00|
|Minimax Lower Bounds||00:20:00|
|Misspecified Linear Models||00:20:00|
|Sub-Gaussian Random Variables||00:30:00|
|Submit Your Assignment||00:00:00|
No Reviews found for this course.