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You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.
You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.
You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.
You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.
What else can I help you with?
How do you compute the probability distribution of a function of two Poisson random variables?
we compute it by using their differences
What type of variables is the number of robberies reported in your city?
discrete
Brand of toothpaste discrete or continuous?
Discrete.
Is the number of pills in a container of vitamins discrete or continuous?
Discrete random variable
Examples of continuous variables?
A continuous variable is one that can take infinite number of values in an interval. Examples are weight, height. A person's weight can be 150.2 lbs, 150.456 pounds and so on. Discrete variables, on the other hand can only assume a finite number of values. For example, number of people in a movie theatre.
What is the difference between continuous and discrete system?
The difference between continuous and discrete system lies in the variables. Whereas the continuous systems have dynamic variables, the discrete system have static variables.
What are continuous and discrete variables?
the value of variables is determined by the equation, discrete variables have absolute single value while the continuos have a range value
Number of notes in a song is discrete variable?
number of notes in a song is discrete variables or continuous variables
Are quiz scores discrete or continuous variables?
Quiz and exam scores are discrete variables because they are defined as one exact number.
Are negative numbers discrete random variables?
Discrete variables must be countable and not negative. So no a negative number must be a continuous variable.
How do you compute the probability distribution of a function of two Poisson random variables?
we compute it by using their differences
What type of variables is the number of robberies reported in your city?
discrete
What type of data has an infinite number of points between each measurement?
I think you are going for continuous variable, as compared with discrete variables.
Should there be equal steps between values in discrete random variables?
Not necessarily.
Is the amount of rain in city B in April a discrete variable?
No, the amount of rain in city B in April is not a discrete variable; it is a continuous variable. Continuous variables can take on any value within a given range, and rainfall can vary in infinitesimal amounts. In contrast, discrete variables represent countable quantities, such as the number of days it rained.
Classification of variables according of continuity of values?
Not continuous => Discrete variable. Continuous => Continuous variable.
What are the pros and cons of discrete probability distribution?
Strictly speaking, there are no cons because they are defined for discrete variables only. The only con that I could think of is the difficulty evaluating the moments and other probabilities for some discrete distributions such as the negative binomial.
