The correct answer is: D. Probability distributions for Continuous variables.
A probability density function (PDF) is a function that describes the probability of a continuous random variable taking on a value within a given interval. It is often represented by the letter $f$, and its integral over a given interval gives the probability that the random variable will take on a value in that interval.
A probability distribution is a mathematical function that describes the possible values of a random variable and the probabilities associated with each value. It is often represented by a graph, with the horizontal axis representing the possible values of the random variable and the vertical axis representing the probabilities.
A continuous variable is a variable that can take on any value within a given range. For example, the height of a person is a continuous variable, because it can take on any value between the minimum and maximum heights of humans.
A discrete variable is a variable that can only take on a finite number of values. For example, the number of children in a family is a discrete variable, because it can only take on the values 0, 1, 2, 3, etc.
Probability distributions for continuous variables are often used in statistics and probability theory. They can be used to model the distribution of data, to make predictions about future events, and to test hypotheses.