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Is the expected value of a discrete random variable equal to the mean of the random variable?
Wiki User
∙ 11y ago
yes?
Wiki User
∙ 11y ago
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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.
How do calculate the probability of at most?
For a discrete variable, you add together the probabilities of all values of the random variable less than or equal to the specified number. For a continuous variable it the integral of the probability distribution function up to the specified value. Often these values may be calculated or tabulated as cumulative probability distributions.
What is the difference between correlation and covariance?
Correlation is scaled to be between -1 and +1 depending on whether there is positive or negative correlation, and is dimensionless. The covariance however, ranges from zero, in the case of two independent variables, to Var(X), in the case where the two sets of data are equal. The units of COV(X,Y) are the units of X times the units of Y. correlation is the expected value of two random variables (E[XY]),whereas covariance is expected value of variations of two random variable from their expected values,
In the discrete probability distribution what is the sum of all probabilities?
The sum should equal to 1.
What is the expected value of the standard normal distribution equal to?
The expected value of the standard normal distribution is equal to the total amount of the value. It is usually equal to it when the value works out to be the same.
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.
Should there be equal steps between values in discrete random variables?
Not necessarily.
How do calculate the probability of at most?
For a discrete variable, you add together the probabilities of all values of the random variable less than or equal to the specified number. For a continuous variable it the integral of the probability distribution function up to the specified value. Often these values may be calculated or tabulated as cumulative probability distributions.
If the outcomes of a random variable follow a Poisson distribution then their?
means equal the standard deviation
How often the value of a random variable is at or below a certain value.?
The probability of a random variable being at or below a certain value is defined as the cumulative distribution function (CDF) of the variable. The CDF gives the probability that the variable takes on a value less than or equal to a given value.
What is commulative frequency distribution?
The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x.
What is the probability that a Poisson random variable x is equal to 5...?
It depends on the parameter - the mean of the distribution.
Which graph is a cumulative frequency graph?
For ungrouped data, the graph for a random variable (rv), X, is usually a line graph whose horizontal axis is the values that the random variable can take, and whose vertical axis is the number of observations (or outcomes) of the random variable that are less than or equal to that value of the rv. For grouped data the graph is usually a corresponding bar graph.
Is there a symbol for average?
Sometimes it is denoted by putting a line above the variable that is being averaged. The "Expectation value" of a random variable - is like a weighted average. I'll explain by way of example: lets say X represents your grades in high school and how much weight should be given to each grade (not all courses are equal). X is a random variable. E[X] or <X> or the Greek letter mu (µ) - are a few of the common symbols for the Expected Value of X - or your weighted average of high school grades.
What is the difference between correlation and covariance?
Correlation is scaled to be between -1 and +1 depending on whether there is positive or negative correlation, and is dimensionless. The covariance however, ranges from zero, in the case of two independent variables, to Var(X), in the case where the two sets of data are equal. The units of COV(X,Y) are the units of X times the units of Y. correlation is the expected value of two random variables (E[XY]),whereas covariance is expected value of variations of two random variable from their expected values,
What does times 3 equal?
Your question is incomplete. You need more information. At the moment you have given 3x, where x is just some random variable.
Is it possible to have 100 percent confidence interval?
Yes. Simply make sure that the interval is greater than or equal to the range of the random variable.
