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Comment Germany 1986 (Score 1) 270

I went to Germany in 1986. My host father taught me a lesson. When I got there the Mark traded 3 to 1 with the $. As the year went, it dropped to less than 2 to 1. German companies liked when the Mark was 3 to 1. That meant it was easier to sell product to America.

This is not new news. It has been know for REALLY long time.

China pegged itself to the $ to maximize its ability to do what it did.

Comment Bull...... (Score 1) 493

They are amuck these researchers. There is validity to the bias. The unfortunate problem for them is that they can't actually fix the problem without making the problem worse.

The problem is being fixed already. It will take at least a generation of teachers to fix. This generation cannot fix it. It may not get fixed next generation either. The tensors in the equation are too tight. Massage them and they blow back in your face.

Comment Re:As one of the few people here... (Score 1) 208

In Orlando, Florida, before cell phones and texting were a problem at all (1992), I used to watch myself go through a dark yellow light and then watch the next 8 cars go through after me. It was so bad that Red lights were almost viewed as green lights because the people on the cross street had to wait for all the people going through red lights before starting, which was just about when their red light started.

Bad driving is everywhere. It doesn't need texting to make it worse. It was already worse.

Comment Re:The BBB For Science (Score 2, Insightful) 86

They are only acting as the authority to point out the problems. There are huge problems in epidemiology. The really useful data gathered by epidemiology is not the positive correlations, it is the non correlations. This presents a rather ugly problem. The data that people find interesting are the positive correlations. With the exception of 1 or 2 studies, these are pretty much worthless. The data that shows a link isn't there is what is really useful. This is the source of all the bad research.

If you look at epidemiological studies, you find lots of RRs, HRs, and ORs (Relative Risk, Hazard Ratio, Odds Ratio). The confounding factor that is ignored is the Survival Ratio. The ratio of the survivors of doing something to the survivors of not doing that something. This number is almost always 99.99...% One exception is lung cancer and smoking. The survival ratio there is 92%. 92% of people who smoke their whole lives do not get lung cancer. (some simplification here).

Comment Oh Look -- (Score -1) 497

Yet another bloke claiming settled.

Lovely RED chart at the top imbuing you with an overwhelming sense of overheating.

Then you find the "proof" of warming down at the bottom. A carefully excised anomalous temperature chart that. 0.5C total range with a tail pointing down.

Plot the temperature folks. It ain't hard. BEST has it available for free.

All you have to do is parse and plot. I have been pawing through the data from each station. Temperature ranges everywhere. Some really cool ones in Eastern Russia. No where can you see increases over the last 150 years. Way to close to a flat line.

What the iowahawk talks about in the averages for schools is relevant to the discussion of temperatures.

Comment Reminded of a Parallel Computing Problem (Score 2) 239

Way back in 1993, I visited an atomic laboratory in Pennsylvania. On the tour, they showed us the 30,000 core computing machine they had purchased several years before. "We still can't program it".

30 seconds later he pointed to the next piece of metal.

This is our 120,000 core computer.

I raised my hand "Why did you buy a 120,000 core machine when you can't even program the 30,000 core machine!"

"Well it's faster."

one of my early lessons in big companies attacking the wrong problem.

Comment Remember to look at the data from a grand view (Score 1) 967

here is a picture of the CRU data they released recently.

ALL OF IT. That red line in the middle is the GISS temperature anomaly. The Orange dots are the simple average of each months data. All of the gray dots are dots experienced somewhere on the planet.

My analysis.

1. GISS temps seem to match CRU temps.
2. The warming visible if you just look at the Anomaly is almost invisible if you look at the range of temperatures.

Basically you have a bunch of people examining the leaves of a tree in a forest and forgetting to keep track of the forest.

The forest does matter.

Comment CRU Data (Score 1) 821

Here is the CRU Date plotted against time.

That is all the data mind you. The gray dots are station data. The GISS Anomaly Temp is in red. The Simple Mean is in Orange. The black on the bottom is the number of measurements taken. The darker the gray dot the more stations reported that temperature.

Yes this is sophomoric, but basically it tells me someone is playing Charting games to make this look terrible.

Comment Programming Languages (Score 1) 250

Learning a new language doesn't take huge amounts of time. Watching the next wave of 'tools' come washing over the side that will make me more productive because it "just does it", makes me laugh. If all anyone does is what the next tool was designed to do, it just does it, but for some reason no one ever wants to stick just with what it does and suddenly I am figuring out how to twist the new tool to do what the inspired people want.

I suspect the real lesson I need to learn well is "Use programming to make your life easier, don't attempt to make a living programming".

Every time I hear a manager say "That's not hard to do is it?", you should be able to do that in a couple of minutes, I cringe.

Comment Re:you mean Mike "HOCKEY STICK" Mann? (Score 0) 961

Here is a chart of the GISS anomaly (in red) plotted over the CRU raw data. This isn't the entire history of the earth of course, but it does represent the raw data associated with the Claim the earth has a fever.

I am not sure I can quite agree that the earth has a fever.

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