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Is the proof in the pudding? Or is it in the data?

Another fitting post over at Seth Godin’s blog:

Folk wisdom and proofiness

“Is it feed a cold, starve a fever, or the other way around, I can never remember?”

Does it matter if you get the rhyme wrong? A folk remedy that doesn’t work doesn’t work whether or not you say it right.

Zig Ziglar used to tell a story about a baseball team on a losing streak. On the road for a doubleheader, the team visited a town that was home to a famous faith healer. While the guys were warming up, the manager disappeared. He came back an hour later with a big handful of bats. “Guys, these bats were blessed and healed by the guru. Our problems are over.”

According to the story, the team snapped out of their streak and won a bunch of games. Some people wonder, “did the faith healer really touch the bats, or was the manager making it up?” Huh? Does it matter?

Mass marketers have traditionally abhorred measurement, preferring rules of thumb, casting calls and alchohol instead. Yet, there’s no real correlation between how the ad was made and how well it works.

As the number of apparently significant digits in the data available to us goes up (traffic was up .1% yesterday!) we continually seek causation, even if we’re looking in the wrong places. As the amount of data we get continues to increase, we need people who can help us turn that data into information.

It’s important, I think, to understand when a placebo is helpful and when it’s not. We shouldn’t look to politicians to tell us whether or not the world is getting warmer (and what’s causing it). They’re not qualified or motivated to turn the data into information. We also shouldn’t look to a fortune teller on the corner to read our x-rays or our blood tests.

Proofiness is a tricky thing. Data is not information, and confusing numbers with truth can help you make some bad decisions.

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how’s the old folk saying go: “give a man a fish feed him for a day; give him a net and watch him trawl the ocean bottom…”

or something like that…

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“Confusing numbers with truth can help you make some bad decisions”… ain’t that the truth, or a fact, or… ummm… set of data…

The curious thing with “data” is that it has a variety of definitions. Some definitions suggest that data is: “a collection of facts from which conclusions may be drawn.”

However, a “fact” is defined in various ways as well, such as: “Knowledge or information based on real occurrences.”

So if we look at, for example, in-season forecasting of Fraser sockeye — there is no shortage of “data”/numbers collected (go visit the Pacific Salmon Commission website to see how many numbers and of what is collected); but, is it “facts”?

No… these are estimates of facts.

Unfortunately, it appears that many institutions have adopted the above definition of “data” — the one that suggests that data is a collection of facts from which conclusions can be drawn.

The big question is: are they the right conclusions?

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There is a better definition of “data” at the Business Dictionary, which suggests it means:

Information in raw or unorganized form (such as alphabets, numbers, or symbols) that refer to, or represent, conditions, ideas, or objects. Data is limitless and present everywhere in the universe.

Also at Wikipedia: “Data (plural of “datum”) are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and then knowledge are derived.”

As such, “data” does not equal “fact” or truth — furthermore, graphs of data does not maketh the truth.

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If data (plural of datum) lies at the lowest level of abstraction from which knowledge is derived… and “knowledge” (a greatly debated term over the ages) might be suggested to mean: “The sum or range of what has been perceived, discovered, or learned.”

Does not a “range” of learning suggest confines?

Confines or borders that can grow over time. Just as any “sum” can grow if something else is added to it — resulting in a new sum.

And so we go back to Godin’s suggestion: “Proofiness is a tricky thing. Data is not information [it is raw and unorganized], and confusing numbers with truth can help you make some bad decisions.”

I would have to say that the history of fisheries management over the last 50 years or so — is wracked with this.

And isn’t it a scary proposition that a politician — the Minister of Fisheries — has such discretionary decision-making power when it comes to fisheries management decisions? (I’m not so sure this has been guided by anything much different than the mass marketers in Godin’s post — nor is there much thought correlation between how the decision was made and how well it worked)

And really, is this much different than the fortune teller on the street corner interpreting our blood tests or x-rays?

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