It is a discrete random variable.

When it is random it is variable.

If x = 1 then X is not really a random variable but a constant.

A random variate is a particular outcome of a random variable: the random variates which are other outcomes of the same random variable would have different values.

True

random variable.

yes?

Random variables is a function that can produce outcomes with different probability and random variates is the particular outcome of a random variable.

A random variable.

A random variable is a function that assigns unique numerical values to all possible outcomes of a random experiment.

A real valued function defined on a sample space of an experiment is also called random variable.

continuous random variable

The discrete random variable almost always arises in connection with counting.

That depends on the rules that define the random variable.

That would be a discrete variable; or, in your case, it would probably be called a discrete random variable.

A random variable is a variable which can take different values and the values that it takes depends on some probability distribution rather than a deterministic rule.

A random process is a process which can be in a number of different states and the transition from one state to another is random.

How often the value of a random variable is at or below a certain value.

Random Variable in probability theory is defined as follows: Assuming you have variables Xi where i is an integer ie: i=1,2,3.......n a variable Xi is called a random variable iff(if and only iff) and random selection yields a variable Xi for i=1,2.........,n with the same likelihood of appearance. i.e prob(X=Xi)=1/n

Yes it is.

· 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.

To find the Z score from the random variable you need the mean and variance of the rv.

To find the Z score from the random variable you need the mean and variance of the rv.

To find the Z score from the random variable you need the mean and variance of the rv.

To find the Z score from the random variable you need the mean and variance of the rv.

A discrete random variable is a variable that can only take some selected values. The values that it can take may be infinite in number (eg the counting numbers), but unlike a continuous random variable, it cannot take any value in between valid results.

A Controlled Variable is a variable that will stay the same. An Uncontrolled Variable is a variable that stays at random during testing.

It depends on what the random variable is, what its domain is, what its probability distribution function is.

The probability that a randomly selected random variable has a value between 40 and 60 is probably quite close to zero.

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.

A random process is a sequence of random variables defined over a period of time.

A Controlled Variable is a variable that will stay the same. An Uncontrolled Variable is a variable that stays at random during testing.

No.

Random

Expected value of a random variable requires that the random variable can be repeated in experiment indefinitely. If the random variable can only be repeated finite times, e.g. once, there is an inadequacy of the expected value principle for a decision maker.

You integrate the probability distribution function to get the cumulative distribution function (cdf). Then find the value of the random variable for which cdf = 0.5.

Yes.

It is a continuous variable. As used in probability theory, it is an example of a continuous random variable.

random, variable, inconstant, unforseeable

It is the Standard normal variable.

A random variable which can take qualitative values rather than numeric values. For example, the question "What colour are your eyes?" will generate qualitative answers.

No. The probability that a continuous random variable takes a specific value is always zero.

Usually we consider a random variable which assigns a value to the outcome of an event. The value assigned to the outcome can be either discrete or continuous. The continuous random variable is a random variable whose domain is defined over a continuous range.

Examples: Daily inches of rain, speed of cars on highway, purchases made everyday at grocery stores.

Random Access Memory (RAM)

the range of values of a random variable.

1.14

Yes.

30.47

Zero.

Flase

In my humble opinion, what people mean with a statistical variable is the same as a random variable, which is explained well in wikipedia: http://en.wikipedia.org/wiki/Random_variable.

A probability density function can be plotted for a single random variable.

A random number is also called a random deviate or pseudo random number. It is a value that is generated by a computer, given a probability distribution. The uniform random number is distributed according to the uniform distribution with values from 0 to 1 and is often used to generate other numbers that follow other distributions. The relative frequency plot of random numbers generated using a particular distribution may not be exactly equal to the particular distribution, due to the limited number of points. But, as the number of random deviates increases, the frequency plot will more closely approximate the given distribution. Random variable have both an intuitive and mathematical definitions. Probability theory is based on sets of events. A throw of coin will have certain outcomes. The random variable, X, links or maps these events to values. A coin can come up heads, so the mapped random variable of this outcome can be 0, and for tails, the random variable of this outcome can be 1. The mathematical definition is a bit more complex- see related links. A random variable is associated with what is considered a random process. If we know the outcome without any uncertainty, we would call it an deterministic process and the outcomes deterministic variables.

There is an exact number of miles for a given route on a trip. However, the measurement of the distance from the odometer some small and possibly random errors, so the measured distances could be considered a continuous random variable.

stochastic demand is random demand. it is determined by predictable actions and a random element.

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.

Suppose a normal random variable has a mean of 72 inches and a standard deviation of 2 inches. Suppose the random variable X measures the height of adult males in a certain city. One may therefore conclude that approximately 84% of the men in this population are shorter than?