[Negitivefrags]

There is no misunderstanding of how probability works here.

100% of people who start businesses believe they can succeed, otherwise they wouldn't start one.

Clearly given that such a high percentage of businesses fail, you are not qualified to judge your own chance at success. Therefore the only time you can know that your percentage chance is higher than the average is when you have a 3rd party that is skilled at evaluating such things that tells you so.

In the absence of such, your chances just fall back to the raw figures that the article gives and so the analysis stands up.

[hluska]

Mind if I jump in with an analogy?

In 2012, the Canadian Olympic team sent 281 athletes to compete at the summer Olympics in London. The World Bank reports that Canada's population is approximately 34,000,000.

Using a raw analysis, you could say that, "A Canadian has a 281/34,000,000 probability of reaching the summer Olympics." That is perfectly valid.

However, you cannot use that same technique to judge individual chances of success. Let's say that I am in a room with Brent Hayden.

Brent Hayden (a swimmer who won a bronze medal) is 6'4 and has a very athletic build. I am 25 pounds overweight, pasty faced from too much time in front of computers and completely void of hand-eye coordination.

Clearly, our individual odds of reaching the Olympics are different. The probability that I will make the summer Olympics is, in actuality, far below 281/34M because I am on the left side of the athletic prowess bell curve. Someone like Brent Hayden's probability of making the summer Olympics in, in actuality, higher than 281/34M because they would fall on the right side of the athletic prowess bell curve.

Those sorts of normal distributions happen in startups as well. Some teams are significantly more suited for the demands of startup lives (just like some couples are significantly better suited for the demands of marriage than others are).

[guylhem]

So what you say with your example is that in a layered sample (say separate the population by heigh or muscle mass), the weighted mean is a better estimator than the arithmetic mean of a sample ?

It is not ignored by statistics. http://en.wikipedia.org/wiki/Weighted_mean

[pg]

Your mistake in turn is to assume that it's impossible for people to judge their own abilities.

Lots of people think they could write a decent novel. Most are wrong. Suppose only .01% actually could. If your argument were correct, JK Rowling should assume her chances of writing a decent novel are .01%. She feels fairly confident that she could, but she has to discount that, because people are often mistaken about such things, and "fall back to the raw figures."

It is possible to know that one is good at something.

[EGreg]

Not only whether one is good at something, but whether they are in a good position to try. If you already have lots of traction, or investors, or smart people around you, then it's a good opportunity.

Having said that, what were the people who funded Color thinking?

[Negitivefrags]

That is not an example of JK Rowling judging her own abilities. Her abilities were judged by the market when she published her books.

It's possible to know one is good at something, it's just not possible to judge your own abilities.

[pg]

I'm not talking about an existing book. I'm talking about the case where she's trying to predict the chance she'll be able to write a new book, before she's started it.

Her previous books should give her confidence that she'll be able to write another. That is one way in which she can judge her own abilities.

[lusr]

What you said is true if you're young and you don't have much data to assess yourself with, but even if you're not pg and don't have a model of success well backed with data, the fact is that if you're 30 or 40 years old there are plenty of objective third parties you will have encountered throughout life who have assessed you for free.

For example, if you've been through a demanding course of tertiary education and performed better than average that says something. Indeed any endeavour that required a fair amount of intelligence, skill, and commitment where you came out above average says something: starting other businesses and having done better than average comes to mind.

In addition to the flaw pg pointed out, the second mistake the article's analysis makes is to ignore the number of opportunities you have; it seems to assume you have a single opportunity. In reality, you can make some less than optimal choices in life and still sometimes do just as fine in the end.

If you're young I don't see what's wrong with gambling a bit: if you're 20 and have zero data about how well you will perform, I believe it's still completely rational to aim high. If you don't get the $100 million exit by 25, you can reconsider your options. After 5 years of aiming high you'll have more than enough data to assess whether it's time to change your aim or to keep going.

[TallboyOne]

I'm no mathematician, or even close, but I don't believe only a person's beliefs translate to their real-world chances of success. A lot has to do with your work ethic, motivation, ability to work long hours, focus, upbringing etc.

I also don't think 100% of people who start businesses believe they can succeed. I'm sure a large percantage are trying to wing it and hope they get lucky.

[Negitivefrags]

I'm not saying that a person's belief translates to their success. In fact I'm saying just the opposite. I would imagine most people starting a business think that their chances are higher than the average person because they are special in some way.

The article is effectively saying "Statistically you are probably not special, so you may want to reconsider taking the risk".

[acgourley]

That's rational. Good luck getting any founder to think that way.

[Negitivefrags]

Well I'm a founder myself and I absolutely did think that we were special and had a much higher chance to succeed than the average person.

Unfortunately at this point it's impossible to know if we were just lucky noobs or actually had some idea what we were doing.