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.

**Assessment**

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.

**Certification**

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.

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: 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 | ||

Assessment | |||

Submit Your Assignment | 00:00:00 | ||

Certification | 00:00:00 |

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