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The Most Dangerous Equation [pdf]

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Re: The Most Dangerous Equation [pdf]

#21
post #3

Absolutely totally true. Ignore the laws of statistics at your own peril. Knowledge of statistics is the best investment one can make with one's time. A/B testing is the tip of the iceberg - a simple practical application, which can be exploited much better with statistics. Learn about statistical distributions - Bernouilli, Binomial, Normal, Poisson and Hypergeometric at least, then Chi distribution to grasp real te…

If someone doesn't know much about statistics what is your recommended source to learn from?

I usually recommend E.T. Jaynes' "Probability Theory: The Logic of Science", which is one of the most beautiful and comprehensive books on the subject.

To get the "logic of science" part, you also need to have (IMHO) some fairly decent grasp of combinatorics, for which I quite recently stumbled upon one of the best books in this field: "Notes on Introductory to Combinatorics." (I like the links to many of Polya's gems of "How to solve it.")

For many other references, a quick HN search for publicly available references will result in other endorsements, too (a preliminary version of the Jaynes' book used to be available, too)

Re: The Most Dangerous Equation [pdf]

#22

Excellent. Reminds me of the lecture describing that "the greatest shortcoming of the human race is our inability to understand the exponential function" http://youtu.be/F-QA2rkpBSY

Thanks for sharing this! Albert Bartlett does a wonderful job explaining the consequences of sustained growth rates.

I find overpopulation to be one of the greatest concerns that we are not adequately dealing with. Albert's bacteria in a bottle analogy made me think of Elon Musk's attempt to bring human life to other planets.. will we not just be expanding our time of growth? Maybe we should start choosing a way to reach a population growth rate of 0% and see what countless problems are resolved.

Re: The Most Dangerous Equation [pdf]

#23
post #15

While statistics are certainly abused an misunderstood, I don't think that small sample sizes are the worst problem. The media usually reports margins of error, and most people know small samples may not represent the population. I think a much larger problem is in the underlying assumptions that are made. For instance, assuming that an experiment on animals can be applied to humans (sometimes it can, sometimes it ca…

The media report margin of error but not confidence interval, which is highly important. If you have a 95% confidence that the poll has a 3% margin, that's a very different statement than 80% confidence.

Re: The Most Dangerous Equation [pdf]

#24
Ah hello law of small numbers, survivorship bias and fundamental attribution error - we meet again. If you understand these 3 biases - you'll wonder what kind of world you have actually been living in all this time.

I'm going to repost a my comment about this very concept as related to startups from a while ago because I believe HNers will appreciate it - it's from an article called "Startup School And Survivor Bias" (hope that's ok :)

Source: http://news.ycombinator.com/item?id=4685042

============================================================

Startups: never have so many understood so little about the statistics of variance present in the outcomes of small samples.

People like to speak of 10x productivity, non-stop work and geniuses - but the reality is much less interesting. A large number of small teams working on many different problems will by definition have a great variance in outcomes just by random extraneous factors (also known as the law of small numbers and insensitivity to sample size).

> A certain town is served by two hospitals. In the larger hospital about 45 babies are born each day, and in the smaller hospital about 15 babies are born each day. As you know, about 50% of all babies are boys. However, the exact percentage varies from day to day. Sometimes it may be higher than 50%, sometimes lower.

For a period of 1 year, each hospital recorded the days on which more than 60% of the babies born were boys. Which hospital do you think recorded more such days?

1) The larger hospital

2) The smaller hospital

3) About the same (that is, within 5% of each other)

56% of subjects chose option 3, and 22% of subjects respectively chose options 1 or 2. However, according to sampling theory the larger hospital is much more likely to report a sex ratio close to 50% on a given day than the smaller hospital.

Relative neglect of sample size were obtained in a different study of statistically sophisticated psychologists

-- http://en.wikipedia.org/wiki/Insensitivity_to_sample_size

> A deviation of 10% or more from the population proportion is much more likely when the sample size is small. Kahneman and Tversky concluded that "the notion that sampling variance decreases in proportion to sample size is apparently not part of man's repertoire of intuitions. For anyone who would wish to view man as a reasonable intuitive statistician such results are discouraging."

-- http://www.decisionresearch.org/pdf/dr36.pdf

Taking lessons as gospel from these "10x" events is by definition foolhardy and merely an extension of the bullshit pushed by the entire "Good To Great" Jim Collins business book industry.

It's like taking lessons from survivors of the Titanic on how to survive the sinking of a ship. It's quite simple - be a young female child with a life vest and rich parents (or in startup land - a young upper-middle class male living in California during a venture bubble, a cyclical investment in the Valley with a convergence of secondary technologies, above average intelligence and a college degree from a reputable university).

I have a personal rule with any kind of advice or explanation coming out of anyone working in a "soft" industry - if it's vague - it's bullshit. All of the advice given at these events are bullshit by this definition. So are many other things - and yeah it doesn't preclude me from spouting it. Or using the advice at my discretion.

But honestly - startup founders literally have no idea why things take off and they have no idea why they win. That's why they have to keep pivoting - it increases their luck surface area and their ability to gain traction - after which they simply must hold on tight while surfing the wave.

YouTube was a dating site - didn't work - pivot - video traction - venture up - ride.

PayPal was a Palm Pilot app - didn't work - pivot - traction - venture up - ride.

Google sold corporate search - didn't work - pivot - copy PPC from Overture - lever up - traction hits - ride.

Instagram - started with a location checking HTML5 app 2 years too early - pivot - copy PicPlz and Hipstamatic - hit traction - lever up - ride.

Angry Birds - fail at hitting nearly every game in the past decade - pivot - take a shot at the iPhone - hits traction - lever up - ride.

Of the startups that didn't pivot - they either skipped the pivot thanks to previous side projects/companies or already had traction - and all they had to do was lever up and ride.

I'm going to make this clear - there is absolutely, positively nothing wrong with this - not at all - it is merely reality and not particularly unfair.

People stating pointless platitudes that success is due to things like "Be 10x more productive", "Commitment" and "People, product, and philosophy" are simply wasting their breath, other people's time and confusing what actually happens. These things may or not be either actionable, predictive or sufficient for success.

Here's my list of startup advice:

Be alive. Be male. Be young. Don't have health issues. Be born in America or move there. Enter the cycle after a recession. Speak English. Enter a growing/new field where the level of competition is low and so is the sophistication of your competition. Surf cost trends down from expensive to mass consumer markets. Work bottom up - on small things. Be of above average intelligence. Have family support. Have a college degree.

Oh and most importantly of all: Get fucking lucky.

The hindsight/survivorship biases in combination with faulty causality and the narrative fallacy will completely hose your thinking - so be careful.

More interesting stuff:

http://en.wikipedia.org/wiki/List_of_biases_in_judgment_and_...

http://en.wikipedia.org/wiki/Black_swan_theory

http://en.wikipedia.org/wiki/List_of_fallacies

http://en.wikipedia.org/wiki/List_of_memory_biases

http://www.econ.yale.edu/~shiller/behfin/2000-05/rabin.pdf

Disclaimer: Biases rule your thoughts and mine - this post is also subject to both bullshit and biases (mostly bullshit - I do love that word). Think for yourself.

Re: The Most Dangerous Equation [pdf]

#25
post #3

Absolutely totally true. Ignore the laws of statistics at your own peril. Knowledge of statistics is the best investment one can make with one's time. A/B testing is the tip of the iceberg - a simple practical application, which can be exploited much better with statistics. Learn about statistical distributions - Bernouilli, Binomial, Normal, Poisson and Hypergeometric at least, then Chi distribution to grasp real te…

If someone doesn't know much about statistics what is your recommended source to learn from?

Khan Academy has a pretty good series of introductory videos:

http://www.khanacademy.org/math/statistics

Re: The Most Dangerous Equation [pdf]

#26

Ah hello law of small numbers, survivorship bias and fundamental attribution error - we meet again. If you understand these 3 biases - you'll wonder what kind of world you have actually been living in all this time. I'm going to repost a my comment about this very concept as related to startups from a while ago because I believe HNers will appreciate it - it's from an article called "Startup School And Survivor Bias"…

Fuck yes. That is why people refer to getting laid as "getting lucky." Thank you for eloquently explaining this, and reposting a link for those of us who missed it the first time around.

Re: The Most Dangerous Equation [pdf]

#27
post #3

Absolutely totally true. Ignore the laws of statistics at your own peril. Knowledge of statistics is the best investment one can make with one's time. A/B testing is the tip of the iceberg - a simple practical application, which can be exploited much better with statistics. Learn about statistical distributions - Bernouilli, Binomial, Normal, Poisson and Hypergeometric at least, then Chi distribution to grasp real te…

If someone doesn't know much about statistics what is your recommended source to learn from?

Probability! The University of Alabama has great resources: www.math.uah.edu/stat/

Re: The Most Dangerous Equation [pdf]

#28

Ah hello law of small numbers, survivorship bias and fundamental attribution error - we meet again. If you understand these 3 biases - you'll wonder what kind of world you have actually been living in all this time. I'm going to repost a my comment about this very concept as related to startups from a while ago because I believe HNers will appreciate it - it's from an article called "Startup School And Survivor Bias"…

Well, apparently Pivoting is like the Monty Hall Problem, so this may be worth a shot

Re: The Most Dangerous Equation [pdf]

#29

Ah hello law of small numbers, survivorship bias and fundamental attribution error - we meet again. If you understand these 3 biases - you'll wonder what kind of world you have actually been living in all this time. I'm going to repost a my comment about this very concept as related to startups from a while ago because I believe HNers will appreciate it - it's from an article called "Startup School And Survivor Bias"…

Also interesting and on topic with this are any of Nicholas Taleb's books. I highly recommend his new one: Antifragile (http://www.amazon.com/gp/aw/d/1400067820)
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