#### Aim of Course:

This course will introduce you to the basic concepts in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

#### Aim of Course:

This course covers clinical trial designs including randomized controlled trials, ROC curves, CI and tests for relative risk and odds ratio, and an introduction to survival analysis.

#### Aim of Course:

To provide an easy introduction to statistical inference for a single variable.

#### Aim of Course:

This course continues the work of Predictive Analytics 1, and introduces you to additional techniques in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

#### Aim of Course:

This course will introduce you to the basic concepts in predictive analytics, also called predictive modeling, the most prevalent form of data mining.

#### Aim of Course:

This course, the second in a three-course sequence, provides an easy introduction to inference and association through a series of practical applications, based on the resampling/simulation approach.

#### Aim of Course:

In this online course, you will learn how to examine data with the goal of detecting anomalies or abnormal instances. This task is critical in a wide range of applications ranging from fraud detection to surveillance.

- Teacher: Nitin Indurkhya