Possible Outcomes when die is rolled
dot showed by die , possible outcome in single roll
thus , formula for the probability distribution of the random variable x will be
P(X=x) = x/6Cx Where as x = 1
x
I will give first the non-mathematical definition as given by Triola in Elementary Statistics: A random variable is a variable typicaly represented by x that has a a single numerical value, determined by chance for each outcome of a procedure. A probability distribution is a graph, table or formula that gives the probabability for each value of the random variable. A mathematical definition given by DeGroot in "Probability and Statistics" A real valued function that is defined in space S is called a random variable. For each random variable X and each set A of real numbers, we could calculate the probabilities. The collection of all of these probabilities is the distribution of X. Triola gets accross the idea of a collection as a table, graph or formula. Further to the definition is the types of distributions- discrete or continuous. Some well know distribution are the normal distribution, exponential, binomial, uniform, triangular and Poisson.
The probability density of the standardized normal distribution is described in the related link. It is the same as a normal distribution, but substituted into the equation is mean = 0 and sigma = 1 which simplifies the formula.
There is no single formula for probability, since there are many different aspects to probability.There is no single formula for probability, since there are many different aspects to probability.There is no single formula for probability, since there are many different aspects to probability.There is no single formula for probability, since there are many different aspects to probability.
Probability equals favorable outcomes divided by total number of outcomes.
I have included two links. A normal random variable is a random variable whose associated probability distribution is the normal probability distribution. By definition, a random variable has to have an associated distribution. The normal distribution (probability density function) is defined by a mathematical formula with a mean and standard deviation as parameters. The normal distribution is ofter called a bell-shaped curve, because of its symmetrical shape. It is not the only symmetrical distribution. The two links should provide more information beyond this simple definition.
The formula, if any, depends on the probability distribution function for the variable. In the case of a discrete variable, X, this defines the probability that X = x. For a continuous variable, the probability density function is a continuous function, f(x), such that Pr(a < X < b) is the area under the function f, between a and b (or the definite integral or f, with respect to x, between a and b.
x
It is the probability distribution function that is relevant for the experiment.
The formula for finding probability depends on the distribution function.
I will give first the non-mathematical definition as given by Triola in Elementary Statistics: A random variable is a variable typicaly represented by x that has a a single numerical value, determined by chance for each outcome of a procedure. A probability distribution is a graph, table or formula that gives the probabability for each value of the random variable. A mathematical definition given by DeGroot in "Probability and Statistics" A real valued function that is defined in space S is called a random variable. For each random variable X and each set A of real numbers, we could calculate the probabilities. The collection of all of these probabilities is the distribution of X. Triola gets accross the idea of a collection as a table, graph or formula. Further to the definition is the types of distributions- discrete or continuous. Some well know distribution are the normal distribution, exponential, binomial, uniform, triangular and Poisson.
thas so true
The probability density of the standardized normal distribution is described in the related link. It is the same as a normal distribution, but substituted into the equation is mean = 0 and sigma = 1 which simplifies the formula.
If a variable X, is distributed Normally with mean m and standard deviation s thenZ = (X - m)/s has a standard normal distribution.
There is no single formula for probability, since there are many different aspects to probability.There is no single formula for probability, since there are many different aspects to probability.There is no single formula for probability, since there are many different aspects to probability.There is no single formula for probability, since there are many different aspects to probability.
The shell formula is a chemical formula that represents the electron configuration of an atom. It is used to describe the distribution of electrons in the various energy levels or shells surrounding the nucleus of an atom. The shell formula typically consists of the symbol of the element, followed by numbers representing the distribution of electrons in each energy level.
The official formula for probability is x/y.