Operations Research Models and Methods / Computation
 Random Variables User Defined Functions

With the Random Variables add-in, several functions are provided for dealing with probability distributions. They are found in the User Defined list of the Excel function list. Each function has the prefix RV. We present below the general definitions below, with examples taken from the dice random variable. The example is shown in both the numerical format and the formula format, so you can see how to enter the functions. Note that the Excel 5-7 versions use different function names. Click here for a description.

## User Defined Functions

Function Purpose

RV_prob(RV,Lower,Upper)

RV_prob(Dice,B8,B9)

Computes the probability that the random variable RV falls between Lower and Upper, inclusive.

In the example the statement points to cells B8 and B9 where the numbers 8 and 10 are stored. The function returns the numerical value of 0.333, the probability that a throw of the dice will yield between 8 and 10, inclusive.

Rather than name the random variable as in the example. The user can select a range that includes the type of random variable and its parameters. The Lower and upper parameters may be left out. For instance

RV_prob(RV,,Upper)

will return the probability that the random variable is less than Upper.

RV_inverse(RV,Prob)

RV_inverse(Dice,B11)

Computes the value of the random variable, such that the probability that RV is less than that value is equal to Prob.

The example points to B11 where the number 0.8 is entered. The value of the cumulative distribution at 9 is 0.8333. The function returns 9 because it is the smallest value whose cumulative distribution exceeds 0.8.

RV_mean(RV)

RV_mean(Dice)

Computes the mean of RV.

RV_var(RV)

RV_var(Dice)

Computes the variance of RV.

RV_skew(RV)

Computes the skewness of RV. This is computed as the third moment about the mean squared, divided by the variance cubed. This method corresponds to the formulas used by Excel to compute the skewness of statistical data.

RV_kurt(RV)

Computes the kurtosis of RV. This is computed as the fourth moment about the mean divided by the variance squared. This method corresponds to the formulas used by Excel to compute the kurtosis of statistical data.

RV_simV(RV)

RV_simV(Dice)

Simulates RV. The function name ending in V indicates that this function is volatile. Each recompute of the worksheet simulates a new value. This is useful in simulation studies.

RV_sim(RV, Seed)

Simulates RV with a seed. This option allows a repeatable sequence of random observations. A negative seed determines the first value. A positive seed gives the next simulated value in a sequence.

Each function has an argument with specifies a range showing the type and parameters of the random variable, shown below as RV. This may be the name of a previously defined random variable. In this case, RV is typed as a word, such as "Dice" (without the quotes).

### Examples of User Defined Functions  RV_prob(RV,Lower,Upper) This function computes the probability that the random variable specified by the first argument falls within the limits specified by the last two arguments. Lower is a number or reference to a number that specifies the lower bound of the range. If no value is specified, Lower is taken as the smallest number the random variable can assume or negative infinity if the random variable is unbounded from below. Upper is a number or reference to a number that specifies the upper bound of the range. If no value is specified, the value is taken as the largest value in the range of the random variable or positive infinity if the random variable is unbounded from above. Several examples are shown below for the Craps game. The first column is the event, the second is the expression entered into the cells, and the third is the value.

 Distribution information may be entered by reference rather than name in the Probability function and the other functions of this section. Say the array of numbers shown below is placed on worksheet in column A. Entering " = RV_prob(A1:A4,2,3) " into a cell computes the probability that the random variable with a discrete triangular distribution will fall between 2 and 3, inclusive. The names for the distributions are the same as those appearing on the Distribution Dialog sheet shown above. Identifying a distribution by reference is useful when the distribution data is entered in a row or column of a spreadsheet.

 RV_inverse(RV,Prob) This function computes the inverse probabilities of defined random variables. The random variable name is specified in the RV argument. The probability is specified in the Prob argument. The function returns the smallest value of x such that P(RV <= x) <= Prob. As an illustration of inverse probabilities assume that the time required for a given activity has a Normal distribution mean of 2.5 hours and a standard deviation of 1 hour. Several examples of inverse probabilities are given below. We ask, how much time must we allow to assure with 90% probability that the activity is complete? From the first of the three examples we conclude that 3.78 hours must be allowed.

 RV_mean(RV)  RV_var(RV)  RV_skew(RV)  RV_kurt(RV) These functions compute four descriptive measures of the distribution. Dice random variable are shown below.

The example below shows the moments computed for a binomial random variable. The negative sign on the skewness indicates that the distribution is skewed to the left. A positive sign indicates a distribution skewed to the right.

 RV_sim(RV, Seed) This function simulates values of the random variable. RV is the name of the random variable, and Seed is a number or reference to a number which is a seed for the internal random number generator of Excel. The table below shows the set of commands that generates a series of four simulated values of the Operating random variable defined above. By providing a negative number as the seed, a repeatable series of simulated values is obtained. This is useful in a many contexts.

 RV_simV(RV) This function simulates values of the random variable. This is a volatile function, in that every time the cell is recalculated, a new simulated value of the random variable RV is presented. No seed is necessary. The example shows the simulation of 5 throws of a pair of dice.

Operations Research Models and Methods
by Paul A. Jensen and Jon Bard, University of Texas, Copyright by the Authors