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**Flat Earth Investigations / Re: Rowbotham experiment #9**

« **on:**January 19, 2019, 02:59:07 PM »

The comment about causation and correlation is another example of “heads I win, tails you lose” reasoning.

The globe model can predict how far one should be able to see objects from if we know their height above sea level. Now, in real life there may be refraction effects which make it harder to predict exactly but some correlation between the maximum distance an object can be seen and the prediction from the model would build confidence in the model.

Rowbotham casts doubt on the model by claiming that there are lots of sightings from much further than predicted by the model. The counter argument presented was that the non-UK data seems to be unreliable and from a different source to UK data and the UK data does actually correlate quite well with the globe earth model.

Then Pete swings in with “correlation doesn’t imply causation”. Now, he’s right but here we are testing a model which claims a correlation. The criticism is that the correlation doesn’t exist, ergo the model is wrong. If someone shows that a correlation does exist for a section of the data and that other data had a different, possibly less reliable source, then that can’t just be dismissed as meaningless

The globe model can predict how far one should be able to see objects from if we know their height above sea level. Now, in real life there may be refraction effects which make it harder to predict exactly but some correlation between the maximum distance an object can be seen and the prediction from the model would build confidence in the model.

Rowbotham casts doubt on the model by claiming that there are lots of sightings from much further than predicted by the model. The counter argument presented was that the non-UK data seems to be unreliable and from a different source to UK data and the UK data does actually correlate quite well with the globe earth model.

Then Pete swings in with “correlation doesn’t imply causation”. Now, he’s right but here we are testing a model which claims a correlation. The criticism is that the correlation doesn’t exist, ergo the model is wrong. If someone shows that a correlation does exist for a section of the data and that other data had a different, possibly less reliable source, then that can’t just be dismissed as meaningless