You get a bonus - 1 coin for daily activity. Now you have 1 coin

Distribution density of a system of two random variables

Lecture



Introduced in the previous   Distribution density of a system of two random variables system characteristic - the distribution function - exists for systems of any random variables, both discontinuous and continuous. The main practical importance are systems of continuous random variables. The distribution of a system of continuous quantities is usually characterized not by a distribution function, but by a distribution density.

Introducing the distribution density for one random variable, we defined it as the limit of the ratio of the probability of hitting a small area to the length of this area with its unlimited decrease. Similarly, we determine the distribution density of a system of two quantities.

Let there be a system of two continuous random variables.   Distribution density of a system of two random variables which is interpreted by a random point on the plane   Distribution density of a system of two random variables . Consider a small rectangle on this plane.   Distribution density of a system of two random variables with the parties   Distribution density of a system of two random variables and   Distribution density of a system of two random variables adjacent to the point with coordinates   Distribution density of a system of two random variables (fig. 8.3.1). The probability of hitting this rectangle by the formula (8.2.2) is equal to

  Distribution density of a system of two random variables

  Distribution density of a system of two random variables

Fig. 8.3.1

Divide the probability of hitting the rectangle.   Distribution density of a system of two random variables on the area of ​​this rectangle and go to the limit at   Distribution density of a system of two random variables and   Distribution density of a system of two random variables :

  Distribution density of a system of two random variables (8.3.1)

Suppose the function   Distribution density of a system of two random variables not only continuous, but differentiable; then the right side of the formula (8.3.1) is the second mixed partial derivative of the function   Distribution density of a system of two random variables by   Distribution density of a system of two random variables and   Distribution density of a system of two random variables . We denote this derivative   Distribution density of a system of two random variables :

  Distribution density of a system of two random variables (8.3.2)

Function   Distribution density of a system of two random variables called the distribution density of the system.

Thus, the distribution density of the system is the limit of the ratio of the probability of hitting a small rectangle to the area of ​​this rectangle, when both of its dimensions tend to zero; it can be expressed as the second mixed partial derivative of the distribution function of the system with respect to both arguments.

If we use the "mechanical" interpretation of the distribution of the system as the distribution of a unit mass over the plane   Distribution density of a system of two random variables function   Distribution density of a system of two random variables is the mass density distribution at   Distribution density of a system of two random variables .

  Distribution density of a system of two random variables

Fig. 8.3.2

Geometrically function   Distribution density of a system of two random variables can be depicted as a surface (Fig. 8.3.2). This surface is similar to the distribution curve for one random variable and is called the distribution surface.

  Distribution density of a system of two random variables

Fig. 8.3.3

If you cross the distribution surface   Distribution density of a system of two random variables plane parallel to the plane   Distribution density of a system of two random variables , and project the resulting section on the plane   Distribution density of a system of two random variables , we get a curve, at each point of which the distribution density is constant. Such curves are called equal density curves. Curves of equal density, obviously, represent the horizontal surface distribution. It is often convenient to set the distribution of a family of curves of equal density.

Considering the density of distribution   Distribution density of a system of two random variables for one random variable, we introduced the concept of "probability element"   Distribution density of a system of two random variables . This is the probability of hitting a random variable.   Distribution density of a system of two random variables on the elementary plot   Distribution density of a system of two random variables adjacent to the point   Distribution density of a system of two random variables . A similar concept of the “probability element” is introduced for a system of two quantities. The element of probability in this case is the expression

  Distribution density of a system of two random variables .

Obviously, the element of probability is nothing but the probability of falling into an elementary rectangle with sides   Distribution density of a system of two random variables ,   Distribution density of a system of two random variables adjacent to the point   Distribution density of a system of two random variables (fig. 8.3.3).

This probability is equal to the volume of the elementary parallelepiped bounded above by the surface   Distribution density of a system of two random variables and based on the elementary rectangle   Distribution density of a system of two random variables (fig. 8.3.4).

Using the concept of an element of probability, we derive an expression for the probability of a random point hitting an arbitrary region   Distribution density of a system of two random variables . This probability can obviously be obtained by summing (integrating) probability elements over the entire region   Distribution density of a system of two random variables :

  Distribution density of a system of two random variables (8.3.3)

Geometrically probability of hitting the area   Distribution density of a system of two random variables depicted by the volume of a cylindrical body   Distribution density of a system of two random variables bounded above the surface of the distribution and based on the area   Distribution density of a system of two random variables (fig. 8.3.5).

  Distribution density of a system of two random variables

Fig. 8.3.4 Figure 8.3.5

The general formula (8.3.3) implies the formula for the probability of hitting the rectangle   Distribution density of a system of two random variables limited by abscissas   Distribution density of a system of two random variables and   Distribution density of a system of two random variables and ordinates   Distribution density of a system of two random variables and   Distribution density of a system of two random variables (fig. 8.3.5);

  Distribution density of a system of two random variables . (8.3.4)

We use the formula (8.3.4) in order to express the distribution function of the system   Distribution density of a system of two random variables through density distribution   Distribution density of a system of two random variables . Distribution function   Distribution density of a system of two random variables there is a chance of falling into an infinite quadrant; the latter can be considered as a rectangle bounded by abscissas -   Distribution density of a system of two random variables and   Distribution density of a system of two random variables and ordinates -   Distribution density of a system of two random variables and   Distribution density of a system of two random variables . By the formula (8.3.4) we have:

  Distribution density of a system of two random variables . (8.3.5)

It is easy to verify the following properties of the distribution density of the system:

1. The distribution density of a system is a non-negative function:

  Distribution density of a system of two random variables .

This is clear from the fact that the distribution density is the limit of the ratio of two non-negative values: the probability of hitting the rectangle and the area of ​​the rectangle — and, therefore, cannot be negative.

2. The double integral in the infinite limits of the distribution density of the system is equal to one:

  Distribution density of a system of two random variables (8.3.6)

This is evident from the fact that the integral (8.3.6) is nothing more than the probability of hitting the entire plane.   Distribution density of a system of two random variables i.e. probability of a reliable event.

Geometrically, this property means that the total volume of the body bounded by the surface distribution and the plane   Distribution density of a system of two random variables , is equal to one.

Example 1. A system of two random variables   Distribution density of a system of two random variables subject to the distribution law with density

  Distribution density of a system of two random variables .

Find distribution function   Distribution density of a system of two random variables . Determine the probability of hitting a random point.   Distribution density of a system of two random variables in square   Distribution density of a system of two random variables (fig. 8.3.6).

  Distribution density of a system of two random variables

Fig. 8.3.6

Decision. Distribution function   Distribution density of a system of two random variables we find by the formula (8.3.5).

  Distribution density of a system of two random variables .

Probability of hitting a rectangle   Distribution density of a system of two random variables we find by the formula (8.3.4):

  Distribution density of a system of two random variables .

Example 2. System distribution surface   Distribution density of a system of two random variables is a straight circular cone, the base of which is a circle of radius   Distribution density of a system of two random variables centered at the origin. Write an expression for the density of distribution. Determine the probability that a random point   Distribution density of a system of two random variables will fall into a circle   Distribution density of a system of two random variables radius   Distribution density of a system of two random variables (fig. 8.3.7), and   Distribution density of a system of two random variables .

  Distribution density of a system of two random variables

Fig. 8.3.7 Figure 8.3.8

Decision. The expression of the density of the distribution inside the circle   Distribution density of a system of two random variables we find from fig. 8.3.8:

  Distribution density of a system of two random variables ,

Where   Distribution density of a system of two random variables - the height of the cone. Magnitude   Distribution density of a system of two random variables determined so that the volume of the cone was equal to one:   Distribution density of a system of two random variables from where

  Distribution density of a system of two random variables ,

and

  Distribution density of a system of two random variables .

Probability of hitting the circle   Distribution density of a system of two random variables determined by the formula (8.3.4):

  Distribution density of a system of two random variables . (8.3.7)

To calculate the integral (8.3.7), it is convenient to go to the polar coordinate system   Distribution density of a system of two random variables :

  Distribution density of a system of two random variables .

created: 2015-01-02
updated: 2021-03-13
132688



Rating 9 of 10. count vote: 2
Are you satisfied?:



Comments


To leave a comment
If you have any suggestion, idea, thanks or comment, feel free to write. We really value feedback and are glad to hear your opinion.
To reply

Probability theory. Mathematical Statistics and Stochastic Analysis

Terms: Probability theory. Mathematical Statistics and Stochastic Analysis