I am a graduate in biology and have worked on a thesis in the humanities titled 'Social science in the age of biology'. It discusses how biologists adopt different approaches to questions pertaining to human behaviour and organisation of society. It piqued my interest in the social sciences.  I have now begun to study some of the works in the social sciences independently and am frustrated by the lack of learning resources online. Time and again, I feel the need for guidance. I am unable to enroll in a university for personal reasons.  Stack Exchange provides a great platform for guided online learning. Is it possible to create a site where questions belonging to the social sciences can be addressed?
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I have an idea or subject that should have a Q&amp;A, and want to propose a new site. How can I do this?  Related:
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For all that is said about the wealth of information that is freely available on the internet, the fact is that most of it is incomplete, dumbed down, lacking in context or downright wrong.   Individuals spend the best part of 20 years completely oblivious to the existence of journals and the process of peer review and even then we'd be lucky if 10% of those with access to journals (usually through an institution) actually bother to invest in them.   Granted that some journals will be totally inaccessible to those without a solid background in some particular field but by and large exposure is a good thing and there are many areas of research where individuals will benefit directly from having read these.  Where does this come from?  I decided I wanted to read Popular Politics in the Late Medieval City: York and Bruge in The English Historical Review today, mainly because it looks interesting and I'm hoping to invest more time into learning about British and European History. Incidentally I also wouldn't mind tucking into Super Stable Clocks, Nature 500, 505 (29 August 2013) and a number of data analysis and big data journals in order to advance my career.   Now, not being affiliated with an institution that subscribes to these journals means that I would typically have to pay between £5 ($10) and £15 ($25) per article that I read... I could probably spend £100 just to pass an hour by.  Question   What's being done to address the lockdown on 'higher' education material? I've noticed that the Directory of Open Access Journals publishes open articles and other firms are doing similar, mainly with journals in new fields? How could I, as an individual outside of an institution, gain journal access without it costing so much money?
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I really love research. I started a research project in graduate school for my M.A. in English. My research topic is a very viable and interesting topic for a dissertation. I'll be 60 on my next birthday and I know that many Ph.D programs are traditionally geared toward younger students.I was wondering are there any programs that I can continue this research in without facing the issues of ageism in academia?
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I have just completed a PhD by research, which I think has some merits in being available as a book (This is, of course, my personal opinion). The research cuts across several fields (e.g. sociology, public policy).  I am wondering what I need to do to take the next step.  In particular:   How do you turn an academic piece like the dissertation (which is written for the examiners) into a book (which is for the general public)? How do I find publishers who specialise in my field?
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I'm embarrassed to say that I have a PhD and hold an asst professorship, but get tripped up when reading statistics research. I am in a field of Business that is similar to IO Psychology or Social Psych. I spend too much time reading applied stats books, but I find even with all the reading I don't have a firm grasp of what I'm actually doing. Everything is very 'seat of the pants.' (As sad as it seems, I think this is not a unique situation among the faculty in the social sciences...) The biggest problem comes when I need to apply a rarely used stat technique. I can find an article from a mathematical stats journal with the equations that would solve my problem, but I don't have the math to convert those into code. I am forever relying on other prof's R packages, and crossing my fingers hoping it will work (I can't even check to verify if it did or not). It's been over 15 years since I took Calculus and Algebra in undergrad, and I think I want to start at the beginning and truly understand probability and statistics.   I am starting with  and  for a quick refresher of the basics -- I know it's hard to believe, but in an applied research field we rarely have use for sin or cos. I'm even trying to finally learn how to correctly do a proof, using the books from Velleman ("") and Houston ("") -- I'm serious about doing this right and understanding the subject. From there I want to move on to (correctly) learn the Calculus and Linear Algebra I need to tackle probability and statistics. I was thinking of using  and  books. But  comes highly recommended as well. After that I am completely at a loss. Further, I don't know how far to go into Calculus or Linear Algebra before I reach diminishing returns. (Apostle introduces Probability in the  -- is it vital that I work through everything preceding it before tackling Probability?)  So my question is: if you had to do it over again with the goal of truly, deeply understanding statistics, where would you start? What books are the modern path to deep understanding? I would like to follow a modern path so that I can understand current research in statistics, including Bayesian approaches. But not in a machine learning context (which seems to be the all the rage at the moment), rather a social science / design and analysis of experiments / multilevel modeling context. Perhaps my goal would be the work of Andrew Gelman;  showed me how I should be looking at modeling and statistics (simulation, uncertainty estimates everywhere, bayesian inference, and so on).  How should I go about relearning this material with that end goal in mind?    Update 1: Possible texts, starting from scratch with a focus on proofs and deep understanding. Not necessarily one after another.  Relearn the basics:    by Velleman  by Houston  and  by Gelfand (for understanding why and how instead of what)  by Simmons (for reference)  by Lockhart (for inspiration)   Calculus (which one(s), and how deep?):    by Strang  and  by Apostol   by Spivak ()   by Curant (and II/1 II/2?)   Linear Algebra (which one(s) and how deep?):    by Strang  by Searle  by Gentle   Probability (which one(s)?):    and  by Feller  (for intuitive understanding)  by Hoel, Port, Stone  by Resnick (for measure theoretic / modern approach?)  by Mosteller   Core Statistics (which one(s)?):    by DeGroot and Schervish  Casella and Berger   Other suggestions? Again with the goal of understanding and developing (or at least implementing) new methods in hierarchical modelling (generalized and linear).
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I did a science PhD doing applied bayesian statistics, and I liked it so much that I decided to shift to statistics.  For the last 2-3 years have been working at a firm that has more of a frequentist focus.  It seems to me that the bayesian approach (at least what I learned) has an underlying theory that was laid out and I could understand.  Now I find this - more classical - field fascinating but I am looking for some resources to get a unified view of the matter.  For example, I am learning and applying anovas, F-tests and chi-squares, thinking about degrees of freedom, etc but part of me is looking for deeper understanding that would make it more than just methods.  Does anyone have any suggestions on books or more resources that provide such a unified, deeper focus?
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My understanding of research is that it's a way to find solutions/answers to questions/problems in a certain subfield of a bigger discipline, which in my case would be Computer Science (honestly, it'd be more like Computer Engineering).  I think I know, however, that if these problems and solutions are too simple or banal, the whole process of doing research is irrelevant because    surely somebody else has already worked in that, and  there's no sense in working in something that won't contribute a significant amount of knowledge to the discipline.    This means that in order to get worthy (or at least relevant) problems to research, you must be at the cutting edge of the field so that you have an idea of what's not yet known and you can start working on it. Am I right?  If I am, that sounds kind of complicated. I have heard that I should read lots of papers in an area of my interest and work from there, but I'm sincerely not sure about how to start doing even this. I have access to the ACM Digital Library, for example, but I don't know what to search for, what to read, or in what order to do so.   I am alone in this, for my university is weak in research and no professors seem to be interested in it. Do you have any tips, or any specific set of steps that you followed to get into research?
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I've not seen this question before, so I'll ask it after feedback I received on .  I've finished my MBA in the UK and was awarded distinction but would like to find a research group to work with. I'm no longer in the UK (or even Europe) and would like to find a research group with which I could work on a telecommuting / remote basis.  My goal here is not for income (though it's OK if it led to some). My goal is to build my research experience with the thought of pursuing a PhD (business / intercultural management / something in that general area). My MBA didn't result in a lot of research guidance  for me so I feel like there are so many things that I don't know and I want to 'fix' that.  Any ideas how someone can find a research group who would be interested in working with someone remotely for free (obviously there is a time and attention commitment from both sides, which is not exactly free)?
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I am taking an online class that requires a textbook to be purchased. I have found the book through my first simple search using the Google search engine. The website where I found the book seems to be foreign and not related to the original authors. Is it ethical for me to use the free version that I have easily found online and not purchase the book? Edit: I think there is a valid distinction between resources found on controversial websites like SciHub and the Google search engine. Furthermore, my intentions were to purchase the book before I stumbled upon it in the first few search results.
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Question:  Are there any guidelines, sources, or examples of good practices for maintaining theorist's research notebook?  Motivation and context:  Maintaining a  is a much advised (if not a vital) tool for doing research. Many do that nowadays also in . While the methods for writing and maintaining a labbook might differ in details, in "dirty-hands" (no offense!) experimental, or field disciplines, the basics are relatively straightforward and clear. The advice tends to boil down to keep a labbook per single topic one works on and then record all the experiments and thoughts related to those experiments into the notebook. Simplifying a lot, in the end, the researcher (team) would compile a paper from the notes in the notebook.  Now situation of a researcher in a more theoretical discipline is strikingly different. Usually one engages in research on several topics at the same time. The problems a researcher works on are often intertwined and one's view on them changes over time, often merging originally separate streams of thought into a single one, or vice-versa. The work revolves not around experiments which would have a clear objective, but rather around currently prepared papers and then "a cloud of ideas". In summary, theorist's workstyle tends to be very non-linear. Maintaining some kind of a notebook is still a good thing, if for nothing else, then for not forgetting about stuff. My question is about how to go about doing it.  I am after a practical tool helping me to archive my thought process for long-term, as well as efficiently manage and keep an overview of the evolution of the several interacting topics I engage in.
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I am hoping you can give me some suggestions. I am teaching in a very diverse (made of minority groups) college and the students are mostly Psychology majors. Most students are fresh from high school but some of them are older returning students above 40. Most of the students have motivational problems and aversion to math. But I am still looking for a book that covers the basic curriculum: from descriptive to sampling and testing all the way to ANOVA, and all in the context of experimental methods. The department requires me to use SPSS in class, but I like the idea of building the analysis in a spreadsheet such as excel.  p.s. the other teachers use a book that I don't like because of the extensive reliance on computational formulae. I find using these computational formulas - rather than the more intuitive and computationally intensive formula that is consistent with the rational and basic algorithm- unintuitive, unnecessary and confusing. This is the book I refer to Essentials of Statistics for the Behavioral Sciences, 7th Edition Frederick J Gravetter State University of New York, Brockport Larry B. Wallnau State University of New York, Brockport ISBN-10: 049581220X Thank you for reading!
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My feed shows questions from all SE sites, most of which are irrelevant to me.  I'm interested in physics, math, and programming, topics I find served well by the SE model.  There are many SE communities I have no interest in and even get annoyed when I see the kinds of questions and answers posted (ie, opinion based answers that are passed off as truths).    It would be much better if I could manually add each site I'd like to see questions from.
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I'm thinking about pursue my studies and doing a PhD in information technology.  My problem is that I would like to create something new (== write code), and focus my thesis on how this new technology works (each component and global interactions), what it can do, and how it can evolves / be improved. I'm not against doing research, reading books and work on theory - but I want to be more practical than theoretical.  I'm starting to think that a PhD is not a valid option if my goal is to develop something new instead of conducting pure research. Am I wrong ?  About my cursus: I will receive my master degree soon (~= 3 months). I come from a highly technical background, with 5 years of programming and project management.    Edit &amp; more information My university doesn't offers PhD courses, thus my supervisor don't care about   my choices. Another consequence is that I have no other choices than to go to another university.
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I've been lurking on this site for several months, and as someone studying higher mathematics independently (i.e., outside of a college/institutional setting), this forum has probably been the best reference for gleaning general information about college-level math.  However, recently I've come to realize that few of the major/popular math textbooks tend to have solutions to the exercises contained within them or available for free/online. As someone without access to a professor or peers who can check the accuracy of my answers, working through book solutions becomes very tedious. How do I know if I am getting the right answers and thus understanding the material? I know people are encouraged to post here for help with challenging problems, but it doesn't seem appropriate to post in a forum such as this to simply check the veracity of answers. In addition, certain books (e.g., Pugh's Real Mathematical Analysis) contain hundreds of exercises throughout the text, and it would be neither plausible nor acceptable to constantly ask for help with problem after problem for an entire textbook.  I am not in school nor do I plan to enroll anytime soon, so there's not really an option of waiting until college to talk things over with someone more knowledgeable about mathematics. I am learning math out of pure curiosity and not in preparation for future classes or career goals, and while there are a plethora of resources available to the independent student of mathematics now more than ever before, being able to assess how well the material is being absorbed remains a difficult obstacle to overcome.
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My stance is that these websites are a great boon to the research community and they were certainly extremely helpful for my research. I think they should be applauded rather than persecuted, and while they may be illegal now, I think a way to make them legal should be found (in the same way I can download articles legally through my university's subscription to all the major publishers and journals).  Can I thank them in the acknowledgements section of my thesis?
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There is . Is the site appropriate for stuff related to requesting frameworks and libraries? Or should we have another site for that (e.g. name it Frameworks Recommendations or stuff alike)?  I can ask stuff there like: I need a software satisfying W, X, Y, and Z, but I'd like -some day- ask like: I need a Python library satisfying W, X, Y, and Z. The audience may be (and perhaps will be) different.    Is that website on-topic for stuff like that? Or should we open another proposal for that?  No: It's not about asking for a giga-dump for subjectivish questions. The linked-to-dupe question was written and answered with an old mindset and without Software Recommendations in mind. Also it does not consider this specific kind of questions but all the crap in one place. So, no,  is not an appropriate dupe mark for this question.
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I am writing several papers in which I use answers which I received in various StackExchange websites. Naturally I would like to acknowlege and thank the SE members that gave the useful answers. But there are many such answers, and each answer is relevant to a different paper.   So, I would like to download all the questions that I asked in the various SE websites, including the answerer names, to an Excel worksheet in which I can organize the questions by subject.  Is this possible?