> Bias and error are not the same as a lack of objectivity.
Say what? Bias is a lack of objectivity, that's how the word is defined. And errors can be managed by a combination of procedural discipline and peer review. In other words, the essentials of science.
> A loaded coin may come up heads 75% of the time. Using that coin to make a decision yields a biased procedure. It's also objective, since the bias is unrelated to the experimenter.
No, never. The outcome of the study is not objective if the experimenter believes the coin to be fair. And if the experimenter knows the coin is unfair, then it's not objective for a different reason.
Objectivity is not a debating point as in post-modernism, it's a prerequisite for science, and with sufficient rigor, it can be established. This is not to argue that this is always true, but it is always possible.
Quote: "Objectivity is a noun that means a lack of bias, judgment, or prejudice."
And your point (b) confuses inaccuracy and variance, which are distinct factors. All your points (a through c) result in an easily definable and scalar error factor, not at all orthogonal.
You realize that "lack of bias" comes from the thesaurus, not the definition of the word, right?
If you want to use an unusual definition of a word in order to make it apply to all errors (rather than only some), be my guest. There is no point disputing definitions. By your definition, you are correct, by the common definition, you are incorrect.
Quotation: "undistorted by emotion or personal bias".
> If you want to use an unusual definition of a word ...
I just proved that I am using the definition of the word. If you're not happy with what dictionaries have to say on this issue, then begin a campaign to change the meaning of "objective".
> There is no point disputing definitions.
So stop doing that. I'm not disputing the accepted definition, I'm simply posting it. Copy, paste.
All the definitions of objectivity describe a property of the experimenter, not the method.
A method can be biased too. Take, for example, the estimator S^2 = (1/n) sum (x[i]-mean(x))^2. This is a biased estimator of the standard deviation, but nevertheless it is objective. It is not influenced by the state of the experimenter at all.
Personal bias contradicts objectivity, but not all bias is personal bias.
Feel free to conflate all errors under one label - those of us who care about getting our measurements right don't have that luxury.
Say what? Bias is a lack of objectivity, that's how the word is defined. And errors can be managed by a combination of procedural discipline and peer review. In other words, the essentials of science.
> A loaded coin may come up heads 75% of the time. Using that coin to make a decision yields a biased procedure. It's also objective, since the bias is unrelated to the experimenter.
No, never. The outcome of the study is not objective if the experimenter believes the coin to be fair. And if the experimenter knows the coin is unfair, then it's not objective for a different reason.
Objectivity is not a debating point as in post-modernism, it's a prerequisite for science, and with sufficient rigor, it can be established. This is not to argue that this is always true, but it is always possible.