I am trying to use alteryx to create a table for a bell curve visual in PowerBI because PowerBI does not have a dynamic table capability (yet).
My initial data is the following (just a sample)
Request ID | Total Time Taken | FY | Created Date |
1 | 5 | 18/19 | 07/18/2019 |
2 | 10 | 18/19 | 07/01/2019 |
3 | 20 | 17/18 | 08/01/2017 |
4 | 30 | 17/18 | 01/01/2018 |
Using the summarize tool, I have performed the following actions on the data:
I then use a formula tool to create the x-3a and x+3a values (i.e. the min and max's of the array for the bell curve) 'x' being the mean and 'a' being the standard deviation.
I then use a generate rows tool to generate the array ranges for each fiscal year.
This results in the following which is what I want.
FY | Min_Created Date-Date Only | Max_Created Date-Date Only | Mean | Standard Dev | Min_Total Time (Business Days) | Max_Total Time (Business Days) | X-3A | X+3a | Value |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -18 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -17 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -16 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -15 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -14 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -13 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -12 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -11 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -10 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -9 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -8 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -7 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -6 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -5 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -4 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -3 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -2 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | -1 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 0 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 1 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 2 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 3 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 4 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 5 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 6 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 7 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 8 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 9 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 10 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 11 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 12 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 13 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 14 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 15 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 16 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 17 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 18 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 19 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 20 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 21 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 22 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 23 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 24 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 25 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 26 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 27 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 28 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 29 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 30 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 31 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 32 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 33 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 34 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 35 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 36 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 37 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 38 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 39 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 40 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 41 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 42 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 43 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 44 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 45 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 46 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 47 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 48 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 49 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 50 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 51 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 52 |
16/17 | 10/3/2016 | 5/31/2017 | 17 | 12 | 0.01 | 113.1 | -18 | 53 | 53 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -10 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -9 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -8 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -7 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -6 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -5 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -4 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -3 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -2 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | -1 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 0 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 1 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 2 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 3 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 4 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 5 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 6 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 7 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 8 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 9 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 10 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 11 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 12 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 13 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 14 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 15 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 16 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 17 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 18 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 19 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 20 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 21 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 22 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 23 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 24 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 25 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 26 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 27 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 28 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 29 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 30 |
17/18 | 6/1/2017 | 5/31/2018 | 10 | 7 | 0.19 | 64.47 | -10 | 31 | 31 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -10 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -9 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -8 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -7 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -6 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -5 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -4 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -3 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -2 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | -1 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 0 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 1 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 2 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 3 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 4 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 5 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 6 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 7 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 8 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 9 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 10 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 11 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 12 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 13 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 14 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 15 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 16 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 17 |
18/19 | 6/1/2018 | 5/31/2019 | 4 | 5 | 0.01 | 49.59 | -10 | 18 | 18 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | -6 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | -5 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | -4 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | -3 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | -2 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | -1 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 0 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 1 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 2 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 3 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 4 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 5 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 6 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 7 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 8 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 9 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 10 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 11 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 12 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 13 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 14 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 15 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 16 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 17 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 18 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 19 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 20 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 21 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 22 |
19/20 | 6/2/2019 | 7/10/2019 | 8 | 5 | 0.02 | 24.56 | -6 | 23 | 23 |
Next, I need to do the following and this is where I am stuck trying to figure out how to do this.
Ultimately in PowerBI, I want to end up with something like the following but also include labels of the Total Time Taken and the counts and percentages but in order to do this, I need to feed PowerBI the table or tables.
Open to any suggestions on how to do this or if potentially there is a better way to do this...
Solved! Go to Solution.
I can get you the next step of the way. Using this formula taken from here, the attached workflow calculates the y values for your bell curves using this formula
which translates to this in Alteryx
1/SQRT(2*pi()*pow([Standard Dev],2))*exp(-pow(([Value]-[Mean]),2)/(2*pow([Standard Dev],2)))
Dan
Thank you! That works perfectly! now just have to figure out how to plot the points to show the average time taken at each point and get the percentages to define the areas.
Reading your link my 'theory' is I could calculate the z-score for each record, then use a standard normal distribution table to determine the percentage and plotting values. Not sure yet how I will make that work, but time to play! If anyone has any ideas in the meantime, I am open to them!
Alright I got it! I took it a step further and also created a Macro so no one else has to try to figure this out with a built-in Standard Normalization Table.
https://gallery.alteryx.com/#!app/Bell%2BCurve/5d3739e0826fd3108052ad22