In this unit you will learn about making conditional statements about random variables. These conditional statements are very basic versions of the machine learning and statistical models that you will create as a data scientist.
As a very brief example, you might make the statement:
- Overall, the expectation of Y is 10; but,
- If X > 5 then the expectation of Y is 15.
In the second part of this unit, you will learn about the conditional expectation function (which is distinct from the conditional expectation operator that we have been working with). This conditional expectation function (which we will refer to throughout as the CEF), turns out to be a very good method of using information to make predictions about data.
To wrap-up the second section, you will learn about a summary of the CEF, the Best Linear Predictor. This function produces prediction that have the smallest mean squared error of any linear function.