Conditional probability and conditional expectation are important concepts in probability theory. When we have partial information, we can calculate probabilities and expectations based on that information. By conditioning on a random variable, we can calculate desired probabilities more effectively. If X and Y have a joint probability density function, the conditional probability density function of X given Y can be defined. This helps us understand how one variable behaves given the value of another variable.