## FAQs

**Statistical PERT is free so you will try using it**

Project managers need better ways of estimating so they can quickly align the expectations of their stakeholders. Executives need better estimates so they can make better decisions. Everyone needs an easier way to communicate their sense of confidence and risk about future uncertainties.

Statistical PERT® is a simple, powerful way to do all of that.

Everything about this site is intended to break down barriers to a better way of estimating. That’s why all SPERT® spreadsheets and templates are licensed using the GNU General Public License (GPL), so you can freely download, use, modify and share everything on this site. That’s why Statistical PERT uses Excel’s built-in statistical functions (so you don’t have to buy anything extra). That’s why this site doesn’t require you to register before downloading, and why this site uses a secured, encrypted connection.

**So how do you make money off this?**

I don’t make any money off this. Statistical PERT is my gift to project managers everywhere, and anyone else who needs to quickly align expectations and make better decisions about future uncertainties. You’re welcome. 🙂 If you choose to watch my Pluralsight course, Easily Estimate Projects Using Statistics and Excel, that will help defray the cost of running this website. I also accept Paypal donations, too. But you’re under no obligation to watch any video or make a donation. Statistical PERT is freely licensed under the GNU General Public License.

If you’re looking for a catch, you can stop looking. There is no catch.

**Statistical PERT uses the normal because it’s good enough**

PERT uses a special form of the ** beta **distribution but Statistical PERT (SPERT®) Normal Edition uses the

**distribution because, for many estimation problems, using the normal distribution is good enough to make a good decision.**

*normal*As long as the bell-shaped curve is only slightly or moderately skewed, Statistical PERT using Excel’s normal distribution functions will still yield results that are comparable to a Monte Carlo simulation of the same uncertainty modeled using the beta distribution. Visit this blog post to learn more.

The key benefit of using the normal distribution is that Excel’s two normal functions, NORM.DIST and NORM.INV, are both useful and very easy to use. PERT provides an estimate for the *mean* argument, and Statistical PERT creates the required *standard deviation* needed by those two Excel functions.

The goal of any estimation effort should be to develop an estimate that is good enough to make a good decision, and that is accurate enough to be within the estimator’s tolerance for error. While using the beta distribution may be more accurate than using the normal distribution for modeling asymmetrical uncertainties, that fact alone is not a good reason to discard using the normal distribution. For many estimation problems–even involving asymmetrical uncertainties–using the normal distribution leads to a “good enough” estimate that is within the estimator’s tolerance for error.

That said, on March 1, 2017, a new edition of Statistical PERT was released that uses Excel’s two beta functions, BETA.DIST and BETA.INV. The Statistical PERT Beta Edition will accurately model skewed probabilities using the beta distribution’s two shape arguments, *alpha* and *beta*. You can visit this site’s Beta Blog to learn more about this new edition of Statistical PERT, and download Version 1 of a SPERT Beta spreadsheet.

**Statistical PERT uses a different formula than PERT does to find a standard deviation. Why?**

Statistical PERT replaces the PERT formula with a different formula that lets the estimator use *subjective judgment*, intuition, emotion, and/or private knowledge to rationally adjust the standard deviation. The SPERT standard deviation formula is: (Max – Min) * RSM, where RSM is the Ratio Scale Multiplier that corresponds to the estimator’s subjective opinion about how likely is the most likely outcome. The SPERT SD formula better conforms the implied distribution curve to a specific uncertainty. You can learn more about this here.

**(Versions 1.3 and earlier) The SPERT template shows both Unskewed and Skewed probabilities. Which do I use?**

Usually, you should rely on the Skewed probabilities. Statistical PERT uses the normal distribution which implies bell-curve symmetry. When a bell-curve is symmetrical, the median, mean and mode (most likely outcome) all have the same value. When a risk is skewed, though, the mean and mode are different. Excel’s two normal distribution functions, NORM.INV and NORM.DIST, use the mean as a required argument, but you can use the mode as a surrogate for the mean if you have a very skewed uncertainty AND you have very high confidence in how likely the most likely outcome really is. In that particular case only, using the Unskewed probabilities will be better than using the Skewed probabilities. In 2017, Statistical PERT-Beta Edition will be released, and this new edition of Statistical PERT will allow you to better model skewed uncertainties. Want to learn more? Check out this blog post.

**Watch a Pluralsight course to learn more**

You can learn more about Statistical PERT® by doing any of the following:

- Watch a Pluralsight course (Normal Edition)
- Check out the Learn More page of this site
- Visit the Statistical PERT YouTube channel
- Visit this site’s blog
- See if I’m presenting at a nearby conference
- Contact me and ask me a question!