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University of Edinburgh

Statistical Predictive Modelling and Applications

University of Edinburgh via edX

This course may be unavailable.

Overview

This course is running for the final time – if you wish to sign up then you must do so by 5 March 2022.

In this course, you will learn three predictive modelling techniques - linear and logistic regression, and naive Bayes - and their applications in real-world scenarios.

The first half of the course focuses on linear regression. This technique allows you to model a continuous outcome variable using both continuous and categorical predictors. This technique enables you to predict product sales based on several customer variables.

In the second half of the course, you will learn about logistic regression, which is the counterpart of linear regression, when the response variable is categorical. You will also be introduced to naive Bayes; a very intuitive, probabilistic modeling technique.

Syllabus

Week 1: Simple Linear Regression
Week 2: Multiple Linear Regression
Week 3: Extensions and Applications
Week 4: Introduction to Naive Bayes
Week 5: Logistic Regression
Week 6: Estimation and Comparison

Taught by

Dr Galina Andreeva and Dr Matthias Bogaert

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