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What is the relation between statistical inference and probability? Statistical inference uses data analysis to presume properties of any probability distribution.

This course will introduce you to the theory and application of modern, computationally-based methods for exploring and drawing inferences from data. You will get the knowledge of re-sampling methods, non-parametric regression, prediction, and dimension reduction and clustering. Specific topics include Monte Carlo simulation, bootstrap cross-validation, splines, local weighted regression, CART, neural networks and so on.


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 the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

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Course Credit: JHSPH Open

Course Curriculum

Review Stuff You Should Know Basics of Probability, the Central Limit Theorem, and Inference 00:05:00
Lecture 1 Introduction to Regression and Prediction 00:10:00
Lecture 2 Overview of Supervised Learning 00:25:00
Lecture 3 & 4 Linear Methods for Regression 00:20:00
Lecture 5 Linear Methods for Classification 00:26:00
Lecture 6 Kernel Methods 00:25:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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