Recommendation requests:
Intro to calculus. I know about derivatives and I can use them and I sort of understand integrals but my knowledge is very fragmented. For instance, I don’t know what half of the notation is supposed to actually represent. Also, I want strategies for solving problems rather than being given a bunch of (apparently) unrelated tools and told to just figure it out.… yea, I didn’t have a good math teacher
Something or other on the scientific method (how to design experiments)
Biology. General, human, micro, intro or advanced… Just trying to make the list more comprehensive
Chemistry. See above.
Physics. There are already some here but I want more topics (thermodynamics is the first that comes to mind).
In recommendations, I would suggest another criteria be added related to learning type. Some books are being praised for their concreteness and others for their topical comprehensiveness and others for their pedagogical comprehensiveness (addresses most common misconceptions etc.) and other sometimes mutually exclusive traits. Just a way of systematizing this and making it easier for people to get the type of book that they are looking for.
Edit:
Another topic: writing. I have read elements of style but I haven’t read anything else on the subject. I would like to see how it compares to other (newer?) books.
I’ve got a recommendation for experimental design/general inference:
Experimental and Quasi-Experimental Designs for Generalized Causal Inference, by Shadish, Cook, and Campbell (2001)
Admittedly, this is the only textbook I’ve ever used that was expressly for experimental design, but I really do think it is superb. Does anyone else have comparison texts for this kind of thing? The validity typology alone is heroic; statistical conclusion validity, internal validity, construct validity, and external validity are each covered in great detail, as are common threats to each of these types of validity.
Recommendation requests: Intro to calculus. I know about derivatives and I can use them and I sort of understand integrals but my knowledge is very fragmented. For instance, I don’t know what half of the notation is supposed to actually represent. Also, I want strategies for solving problems rather than being given a bunch of (apparently) unrelated tools and told to just figure it out.… yea, I didn’t have a good math teacher
Set theory and other discrete mathematics.
Psychology.
Something or other on the scientific method (how to design experiments)
Biology. General, human, micro, intro or advanced… Just trying to make the list more comprehensive
Chemistry. See above.
Physics. There are already some here but I want more topics (thermodynamics is the first that comes to mind).
In recommendations, I would suggest another criteria be added related to learning type. Some books are being praised for their concreteness and others for their topical comprehensiveness and others for their pedagogical comprehensiveness (addresses most common misconceptions etc.) and other sometimes mutually exclusive traits. Just a way of systematizing this and making it easier for people to get the type of book that they are looking for.
Edit: Another topic: writing. I have read elements of style but I haven’t read anything else on the subject. I would like to see how it compares to other (newer?) books.
Re: how to design experiments:
Look into statistics. Most experiments have a statistical or hidden statistical basis.
See my suggestions above for calculus.
I’ve got a recommendation for experimental design/general inference:
Experimental and Quasi-Experimental Designs for Generalized Causal Inference, by Shadish, Cook, and Campbell (2001)
Admittedly, this is the only textbook I’ve ever used that was expressly for experimental design, but I really do think it is superb. Does anyone else have comparison texts for this kind of thing? The validity typology alone is heroic; statistical conclusion validity, internal validity, construct validity, and external validity are each covered in great detail, as are common threats to each of these types of validity.