subject: Random Variables Statistics [print this page] Introduction to random variables statistics:
Statistical means that the learning about the mean, mode, median and also range. The statistics are the process of the design of the survey and also the experiments. Statistics has the measure find for the data. Statistics has the data collection, analysis and also the interpretation. Statistics is used to decide the population analysis. Statistics has the collection, analysis of the data. Random variable is the measurable function that refers outcomes. Random variables include the discrete and also the continuous random variables.
Types of Random Variables in Statistics:
The types of the variables in statistics are
Discrete random variables:
Random variable maps the events to the values to the countable set of the integers. Discrete random variables are the random variables that take the countable numbers only. There are two types of discrete random variables. They are finite discrete random variable and also the infinite discrete random variable.
Finite discrete random variables:
Finite random variable takes the values as the countable values. For example tossing two coins let x be the random variable that takes account of the possibilities of the head. X is the finite random variable that contains the value of 0, 1, 2.
Infinite discrete random variables:
Infinite discrete random variable takes the infinite values when an experiment is performed. While rolling the die the random variable X denotes the number of trials for rolling the die. The random variable value X can be 1, 2, 3, 4, 5, 6 . . . . . . .
Continuous random variable:
The continuous random variable takes the values as the continuous values. The continuous random variable values are in the continuous interval. It is used to measure the length of the objects. For example, measure the height of the wall.
Examples for the Random Variables Statistics:
Examples 1 for the random variables statistics:
A die is thrown until 6 is obtained. Compute the probability density function for the die.
Solution:
The X represents the number of times rolling the die.
P(X = 1) = '1/6' (If we get the number 6 in the first trial itself).
P(X = 2) =' 5/6' (If we get the number 6 in the second trial itself).
The number of possibilities are P(X = x) = ('5/6' )(n-1) ('1/6)' .
Examples 2 for the random variables statistics:
A die is thrown until 6 is obtained. Compute the probability density function for P(x = 2).
Solution:
The probability for die 6 obtained is P(x = 0) = 0, P(x = 1) = '1/6' , P(x = 2) = '1/6' .
P(x = 2) = 0 + '1/6' + '1/6'
P(x = 2) = '2/6'
P(x = 2) = '1/3'
The probability density function for P(x = 2) = '1/3' .
