I said progress was stagnant, not regressing. All of Darwin’s books have always been widely available and read, so no information was ever lost. Some of Darwin’s conjectures were deemphasized, and the biologists of the time were right to do so; they didn’t yet have the techniques to prove or disprove them, and mere conjecture should never be foundations of a scientific discipline. They weren’t central to the theory anyway, and even Darwin considered them just speculation.
With modern technical know-how, such as radiometric dating and molecular clocks, they’ve discovered evidence supporting some of Darwin’s more difficult-to-prove ideas, such as punctuated equilibrium. Darwin was an exceedingly smart man, so it’s no surprise that some of his idle speculation turned out to be accurate. But that’s a far cry from modern evolutionists “catching up” with Darwin.
I’m not necessarily trying to conivince you of anything, just interested. Assuming that you are convinced that Bayesian statistics are the correct way to treat uncertainty, would you say that the field of statistics never regressed in that respect because the works of Bayes and Laplace were always around?
All of Darwin’s books have always been widely available and read, so no information was ever lost.
That’s a pretty good argument for reading the work of the old masters though, isn’t it? (Not that you voiced any disagreement with that)
You have me at a disadvantage because I don’t know much about the history of statistics, but here is my view. Assuming the core principles of Bayesian statistics were demonstrably effective, if they were widely accepted and then later rejected or neglected for whatever reason, then that would be regression. If Bayes’ and Laplace’s methods never caught on at all until a long time later, and there were no other significant advances in the field, then that would be stagnation.
By these (admittedly my own) definitions, evolutionary biology didn’t regress after Darwin because the only parts of his theory that were neglected were the ones that weren’t yet provable. It’s as if, theoretically, Bayes came up with a variety of statistical methods, most of which were clearly effective but others were of dubious utility. It wouldn’t count as a regression, at least to me, if later generations dropped the dubious methods but kept the useful ones.
That’s a pretty good argument for reading the work of the old masters though, isn’t it?
I apologize, I haven’t made my position clear about this. I think that experts should read the classics as well as modern works in their field. The interested amateur, though, should skip over the classics and go directly to modern thought, unless he or she has more free time than most.
I said progress was stagnant, not regressing. All of Darwin’s books have always been widely available and read, so no information was ever lost. Some of Darwin’s conjectures were deemphasized, and the biologists of the time were right to do so; they didn’t yet have the techniques to prove or disprove them, and mere conjecture should never be foundations of a scientific discipline. They weren’t central to the theory anyway, and even Darwin considered them just speculation.
With modern technical know-how, such as radiometric dating and molecular clocks, they’ve discovered evidence supporting some of Darwin’s more difficult-to-prove ideas, such as punctuated equilibrium. Darwin was an exceedingly smart man, so it’s no surprise that some of his idle speculation turned out to be accurate. But that’s a far cry from modern evolutionists “catching up” with Darwin.
I’m not necessarily trying to conivince you of anything, just interested. Assuming that you are convinced that Bayesian statistics are the correct way to treat uncertainty, would you say that the field of statistics never regressed in that respect because the works of Bayes and Laplace were always around?
That’s a pretty good argument for reading the work of the old masters though, isn’t it? (Not that you voiced any disagreement with that)
You have me at a disadvantage because I don’t know much about the history of statistics, but here is my view. Assuming the core principles of Bayesian statistics were demonstrably effective, if they were widely accepted and then later rejected or neglected for whatever reason, then that would be regression. If Bayes’ and Laplace’s methods never caught on at all until a long time later, and there were no other significant advances in the field, then that would be stagnation.
By these (admittedly my own) definitions, evolutionary biology didn’t regress after Darwin because the only parts of his theory that were neglected were the ones that weren’t yet provable. It’s as if, theoretically, Bayes came up with a variety of statistical methods, most of which were clearly effective but others were of dubious utility. It wouldn’t count as a regression, at least to me, if later generations dropped the dubious methods but kept the useful ones.
I apologize, I haven’t made my position clear about this. I think that experts should read the classics as well as modern works in their field. The interested amateur, though, should skip over the classics and go directly to modern thought, unless he or she has more free time than most.