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What is the difference between a random variable and random process?
A random process is a sequence of random variables defined over a period of time.
What is the difference between a discrete and continuous random variable?
· A variable whose values are determined by the outcomes of a random experiment is called a random variable. A random variable is a discrete random variable if it can assume values, which are finite or countable infinite. For example, tossing of a die is a random experiment and its outcomes 1, 2, 3, 4, 5 and 6 are discrete random variable. When a coin is tossed, its outcomes head and tail are discrete random variable. Three coins are thrown; the number of heads is example of discrete random variable. Note that the outcomes need ot be integers or even numbers (eg colour of eyes). · If a random variable can assume every possible value in an interval [a, b], a< b, where a and b may be - infinity and + infinity respectively, for example, the points on number line between 0 and 1; Value of 'x' between 0 and 2; Number of heads on a coin when it is tossed infinite times.
What are the types of variables in statistics?
dependent variables, independent variable, nominal, ordinal, interval, ratio variableThere are three main kinds:Nominal: such as colour of eyes, or gender, or species of animal. With nominal variables there is no intrinsic sense in which one category can be said to be "more" than another.Ordinal: Such as Small/Medium/Large, orStrongly Disagree/Disagree/Indifferent/Agree/Srongly Agree. The categories can be ordered but the differences between pairs is not comparable. For example, it is not really possible to say that the difference betwen Strongly disagree and disagree is the same as (or double or half or whatever) the difference between indifferent and agree.Interval: These are variables where the distance between one pair of values (their interval) can be related to the distance between another pair. Such variables can be subdivided into discrete and continuous.Another way of classifying variables is independent and dependent.The dependent variable is a random variable but the independent variable can be random or non-random.
Kinds of variables used in statistics?
There are three main kinds:Nominal: such as colour of eyes, or gender, or species of animal. With nominal variables there is no intrinsic sense in which one category can be said to be "more" than another.Ordinal: Such as Small/Medium/Large, orStrongly Disagree/Disagree/Indifferent/Agree/Srongly Agree. The categories can be ordered but the differences between pairs is not comparable. For example, it is not really possible to say that the difference betwen Strongly disagree and disagree is the same as (or double or half or whatever) the difference between indifferent and agree.Interval: These are variables where the distance between one pair of values (their interval) can be related to the distance between another pair. Such variables can be subdivided into discrete and continuous.Another way of classifying variables is independent and dependent.The dependent variable is a random variable but the independent variable can be random or non-random.
Why are important in random variables?
It might help if you specified why WHAT was important in random variables.
Are negative numbers discrete random variables?
Discrete variables must be countable and not negative. So no a negative number must be a continuous variable.
What has the author Wai Wan Tsang written?
Wai Wan Tsang has written: 'Analysis of the square-the-histogram method for generating discrete random variables' -- subject(s): Random variables
Is the gender of college students a discrete random variable a continuous random variable or not a random variable?
It is a discrete random variable.
Definition for decision models and decision variables?
Decision variables are the variables within a model that one can control. They are not random variables. For example, a decision variable might be: whether to vaccinate a population (TRUE or FALSE); the amount of budget to spend (a continuous variable between some minimum and maximum); or how many cars to have in a car pool (a discrete variable between some minimum and maximum).
What is the difference between discrete and cumulative distributions?
A discrete distribution is one in which the random variable can take only a limited number of values. A cumulative distribution, which can be discrete of continuous, is the sum (if discrete) or integral (if continuous) of the probabilities of all events for which the random variable is less than or equal to the given value.
What is discrete probability and what role could it play in your work environment?
Discrete probability is probability in the context of random variables that can only take a discrete number of values. In the work environment there are some events that can have discrete outcomes and others that are continuous. For example, the number of customers in a day (or month) is a discrete variable. The amount that each one spends on your products is discrete. But the time interval between them is not. So the role that any kind of probability could play depends on what you wish to study.
What is the difference between a probability mass function and a probability density function?
The probability mass function is used to characterize the distribution of discrete random variables, while the probability density function is used to characterize the distribution of absolutely continuous random variables. You might want to read more about this at www.statlect.com/prbdst1.htm (see the link below or on the right)
What is the definititon of a discrete random variable?
The discrete random variable almost always arises in connection with counting.
What is the difference between a random variable and random process?
A random process is a sequence of random variables defined over a period of time.
Is the number of pills in a container of vitamins discrete or continuous?
Discrete random variable
What is the difference between a discrete and continuous random variable?
· A variable whose values are determined by the outcomes of a random experiment is called a random variable. A random variable is a discrete random variable if it can assume values, which are finite or countable infinite. For example, tossing of a die is a random experiment and its outcomes 1, 2, 3, 4, 5 and 6 are discrete random variable. When a coin is tossed, its outcomes head and tail are discrete random variable. Three coins are thrown; the number of heads is example of discrete random variable. Note that the outcomes need ot be integers or even numbers (eg colour of eyes). · If a random variable can assume every possible value in an interval [a, b], a< b, where a and b may be - infinity and + infinity respectively, for example, the points on number line between 0 and 1; Value of 'x' between 0 and 2; Number of heads on a coin when it is tossed infinite times.
What is the difference between random variable and random variate?
Random variables is a function that can produce outcomes with different probability and random variates is the particular outcome of a random variable.
