This new build of the SPERT-Beta template adds quite a few new features. I’ve added ratio scales for standard deviation and mean, so the template will calculate an estimate of standard deviation, variance, and mean for each 3-point estimate that’s entered.
Using that information, the template calculates the mean for the entire portfolio being estimated, and the standard deviation for the entire portfolio (by taking the square root of the sum of variances).
And using THAT information, I’ve added the ability to find a confidence interval for the portfolio, which calculates a minimum and maximum estimate values for the entire portfolio.
To test this, build, I created four estimates:
- 100, 400, 500 (Low confidence)
- 200, 500, 1000 (Very low confidence)
- 500, 500, 5000 (Medium-low confidence)
- 1000, 10000, 12000 (Very high confidence)
The result was a portfolio having a SPERT-Beta-estimated mean of 11,878 with a standard deviation of 2,178. The SPERT-Beta 90% confidence interval was 8,294 – 15,461.
Comparing this to a simulation model, I used 10,000 trials and the same 3-point estimates and combination of the SPERT worksheet’s choice for the shape parameters, alpha and beta. In the simulation, the standard deviation was extremely close: 2,180. The 90% confidence interval was a little different: 7,991 – 15,222. The minimum threshold value in the simulation differed by almost 4% from the SPERT-Beta minimum threshold (the SPERT-Beta worksheet overstated the minimum). The maximum threshold value in the simulation differed by only 1.6% from the SPERT-Beta maximum value (again, the SPERT-Beta worksheet overstated the maximum).
In looking at the simulation results, I could see that the portfolio of four estimates was bell-shaped but skewed to the left, slightly, which explains why the SPERT-Beta confidence interval differed from the simulation model. Had I used more than just four 3-point estimates, and had the portfolio exhibited a more normal appearance overall, the SPERT-Beta confidence interval for the portfolio would create results that are closer to the simulation model.
Download Development Release D and view standard deviations, variances, means, and find a confidence interval of your choice using lucky Build 13!
(Visit the Download page to download the latest version of Statistical PERT – Beta Edition).