About Negative Parallax.
Posted: 14.08.2007, 20:46
In this topic: Full-time on Celestia! (http://www.celestiaproject.net/forum/viewtopic.php?t=11207&postdays=0&postorder=asc&start=75), someone raised the matter of negative parallaxes. I've put this post here because it's not to do with the original matter of that topic.
This is an important matter in using statistics for scientific analysis in astronomy, biology and even physics. The reporting of a negative parallax in a star catalogue is correct, even though it must obviously not be true. It is not correct to, er, correct the parallax to zero or positive just because it was measured as negative. I'll explain why in a moment.
The reason a parallax can turn up negative is simple. Errors can cause a star position to off by any direction. During the six months we measure the parallax, we expect the star's position to shift from A to B. In this case, the true parallax was about the same size as a typical error, but the first error pushed the position reading to roughly where B is, and the second error pushed the star to roughly where A is. So the star appears to move from B to A instead of A to B: the parallax is the wrong way round. We can't know what the error was, so we can't subtract those.
Now, you can't eliminate these 'spurious' measurements from a statistical analysis because such filtering will bias any results.
It might be better explained with this curious example. A physics department's nuclear group proudly displays a graph showing the increase of heavy metal inside a worker during working life: the concentrations being found by radio-isotope measurements of factory workers who voluteered. The duration starts at 0 years for beginning of work, and the concentration is in parts per million (ppm). The rise is linear. So far, so good. Then I noticed that the first data point was for a concentration of -5 ppm. Yup, minus!
"How?" I asked the head of department.
"Ah well, you see, you have to measure control volunteers who don't work in the factory and subtract their concentrations from the subjects'. Some controls have more cadmium in them naturally than some factory workers on their first day. The difference gives a negative concentration. You can't correct it to zero, because that would bias the slope of the line and give the wrong result."
"Ah!"
It's also explainable with the infamous Nature paper by Jacques Benevenist 'proving' homeopathy: the negative white blood cell counts between control and subject that he corrected to zero on the grounds that the treated subject cannot react less than the untreated control.
Spiff.
This is an important matter in using statistics for scientific analysis in astronomy, biology and even physics. The reporting of a negative parallax in a star catalogue is correct, even though it must obviously not be true. It is not correct to, er, correct the parallax to zero or positive just because it was measured as negative. I'll explain why in a moment.
The reason a parallax can turn up negative is simple. Errors can cause a star position to off by any direction. During the six months we measure the parallax, we expect the star's position to shift from A to B. In this case, the true parallax was about the same size as a typical error, but the first error pushed the position reading to roughly where B is, and the second error pushed the star to roughly where A is. So the star appears to move from B to A instead of A to B: the parallax is the wrong way round. We can't know what the error was, so we can't subtract those.
Now, you can't eliminate these 'spurious' measurements from a statistical analysis because such filtering will bias any results.
It might be better explained with this curious example. A physics department's nuclear group proudly displays a graph showing the increase of heavy metal inside a worker during working life: the concentrations being found by radio-isotope measurements of factory workers who voluteered. The duration starts at 0 years for beginning of work, and the concentration is in parts per million (ppm). The rise is linear. So far, so good. Then I noticed that the first data point was for a concentration of -5 ppm. Yup, minus!
"How?" I asked the head of department.
"Ah well, you see, you have to measure control volunteers who don't work in the factory and subtract their concentrations from the subjects'. Some controls have more cadmium in them naturally than some factory workers on their first day. The difference gives a negative concentration. You can't correct it to zero, because that would bias the slope of the line and give the wrong result."
"Ah!"
It's also explainable with the infamous Nature paper by Jacques Benevenist 'proving' homeopathy: the negative white blood cell counts between control and subject that he corrected to zero on the grounds that the treated subject cannot react less than the untreated control.
Spiff.