Random numbers generator in Excel

Although Excel’s Data Analysis Toolpak can generate good random numbers, I had to create these various functions to meet my specific needs.

First: Generating Unique Random Numbers

This function was modified from ozgrid’s RandLotto function, which returns a string of numbers without duplicates. This function will return an array of unique random integers that are between the specified range. To return more than one number, enter this function as an array formula with Ctrl + Shift + Enter.

Function UniqueRand(lngSmallest As Long, lngHighest As Long, HowManyNos As Long) As Long()
'modified from http://www.ozgrid.com/VBA/RandomNumbers.htm
    Dim iArr As Variant
    Dim i As Integer
    Dim r As Integer
    Dim temp As Integer
    ReDim iArr(lngSmallest To lngHighest)
    For i = lngSmallest To lngHighest
        iArr(i) = i
    Next i
    For i = lngHighest To lngSmallest + 1 Step -1
        r = Int(Rnd() * (i - lngSmallest + 1)) + lngSmallest
        temp = iArr(r)
        iArr(r) = iArr(i)
        iArr(i) = temp
    Next i
    Dim resultArr() As Long: ReDim resultArr(HowManyNos - 1, 0)
    For i = lngSmallest To lngSmallest + HowManyNos - 1
        resultArr(j, 0) = iArr(i)
        j = j + 1
    Next i
    UniqueRand = resultArr
End Function

Second: Generating Gaussian or Normal Random Numbers with specified mean and Standard deviation(SD).

Now, this function is different from the Analysis toolpak utility, because the utility generates random numbers using a fixed mean and standard deviation. This function will, however, allow the user to generate random numbers with a different mean and SD.

'This function will generate Gaussian or Normal Random Numbers based on given mean and SD
Public Function GenGaussNoise(mean As Double, SD As Double, HowMany As Long) As Double()
Dim x As Double, i As Long, j As Long
itr = 50
Dim dblResArr() As Double: ReDim dblResArr(HowMany - 1, 0)
For j = 1 To HowMany
    x = 0
    For i = 1 To itr
        U = Rnd
        x = x + U
    Next i
    ' /* for uniform randoms in [0,1], mu = 0.5 and var = 1/12 */
    ' /* adjust X so mu = 0 and var = 1 */
    x = x - itr / 2             ' /* set mean to 0 */
    x = x * Sqr(12 / itr)     '  /* adjust variance to 1 */
    dblResArr(j - 1, 0) = mean + SD * x
Next j
    GenGaussNoise = dblResArr
End Function

Third: Generate white noise or Guassian or Normal random numbers with mean = 0 and SD =1.

Although this could be achieved by the previous function, this function uses Box-Muller method. As with the previous function, you can use different mean and SD, but would default to mean =0 and SD=1.

Public Function GenWhiteNoise(HowMany As Long, Optional mean As Double = 0, Optional variance As Double = 1) As Double()
'Returns a normally distributed random variate with mean 0 and variance 1, a.k.a. "White Noise".
'  Uses the Box-Muller method
    Dim Value1 As Single, Value2 As Single, Fac As Single, Rsq As Single, SD As Double
    Dim dblResArr() As Double: ReDim dblResArr(HowMany - 1, 0)
    SD = Sqr(variance)
    For i = 1 To HowMany
            Value1 = 2 * Rnd - 1
            Value2 = 2 * Rnd - 1
            Rsq = Value1 ^ 2 + Value2 ^ 2
        Loop Until Rsq > 0 And Rsq < 1
        Fac = (-2 * Log(Rsq) / Rsq) ^ 0.5
        If Rnd > 0.5 Then
            dblResArr(i - 1, 0) = mean + SD * Value1 * Fac
            dblResArr(i - 1, 0) = mean + SD * Value2 * Fac
        End If
    Next i
    GenWhiteNoise = dblResArr
End Function


to an Excel file with all these generators now!

With this file, you can start generating random numbers right now.


You can see this random number generator in action.

Generate random numbers (unique, Gaussian, white noise) in Excel

Random number generator

About the Author

The author of Tableau Data Visualization Cookbook and an award winning keynote speaker, Ashutosh R. Nandeshwar is one of the few analytics professionals in the higher education industry who has developed analytical solutions for all stages of the student life cycle (from recruitment to giving). He enjoys speaking about the power of data, as well as ranting about data professionals who chase after “interesting” things. He earned his PhD/MS from West Virginia University and his BEng from Nagpur University, all in industrial engineering. Currently, he is leading the data science, reporting, and prospect development efforts at the University of Southern California.

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