A
discrete variable
is a variable whose value is obtained by counting. A continuous variable is a variable whose value is obtained by measuring. A random variable is a variable whose value is a numerical outcome of a random phenomenon. … A continuous random variable X takes all values in a given interval of numbers.
Can a discrete random variable be continuous?
Random variables can be classified as either discrete (that is, taking any of a specified list of exact values) or as
continuous
(taking any numerical value in an interval or collection of intervals).
Is the random variable discrete or continuous explain?
The random variable is
discrete
, because it has a countable number of possible outcomes.
Which is a discrete random variable?
A discrete random variable is
one which may take on only a countable number of distinct values
such as 0,1,2,3,4,…….. Discrete random variables are usually (but not necessarily) counts. If a random variable can take only a finite number of distinct values, then it must be discrete.
Is the a discrete random variable a continuous random variable or not a random variable quizlet?
Is the last book a person in City Upper A read a discrete random variable, continuous random variable, or not a random variable?
It is not a random variable
.
Is the time it takes to fly from city A to city Ba discrete random variable?
(c) Is the time it takes to fly from City A to City B discrete or continuous?
The random variable is continuous
.
Is time continuous or discrete?
Time is
a continuous variable
. You could turn age into a discrete variable and then you could count it. For example: A person’s age in years.
How do you know if a variable is discrete or continuous?
A
discrete variable
is a variable whose value is obtained by counting. A continuous variable is a variable whose value is obtained by measuring. A random variable is a variable whose value is a numerical outcome of a random phenomenon. A discrete random variable X has a countable number of possible values.
What are examples of continuous random variables?
In general, quantities such
as pressure, height, mass, weight, density, volume, temperature, and distance
are examples of continuous random variables.
What are examples of discrete and continuous variables?
| Discrete Variable Continuous Variable | Examples: Number of planets around the Sun Number of students in a class Examples: Number of stars in the space Height or weight of the students in a particular class |
|---|
Which variables Cannot be negative?
But a
non-negative random variable
can be zero. A non-negative random variable is one which takes values greater than or equal to zero with probability one, i.e., X is non-negative if P(X≥0)=1. A negative random variable is one which takes values less than zero with probability one, i.e., Y is negative if P(Y<0)=1.
What is the similarities of continuous and discrete variable?
Discrete variables are the variables, wherein the values can be obtained by counting. On the other hand, Continuous variables are the random variables that measure something.
Discrete variable assumes independent values
whereas continuous variable assumes any value in a given range or continuum.
Which is not a discrete random variable?
Blood type
is not a discrete random variable because it is categorical. Continuous random variables have numeric values that can be any number in an interval. For example, the (exact) weight of a person is a continuous random variable. … Continuous random variables are often measurements, such as weight or length.
Which one is not a continuous variable?
Height
is not an example of a continuous variable.
How do you find the mean of a discrete random variable?
The mean μ of a discrete random variable X is a number that indicates the average value of X over numerous trials of the experiment. It is computed using the formula
μ=∑xP(x)
.
What is discrete probability?
A discrete probability distribution
counts occurrences that have countable or finite outcomes
. This is in contrast to a continuous distribution, where outcomes can fall anywhere on a continuum. Common examples of discrete distribution include the binomial, Poisson, and Bernoulli distributions.
