I am doing a research about the ethics in pharmaceutical industry. I've chosen 7 branding activities followed by pharmaceutical companies.   I want to study the relationship between the perception of ethics in those activities by doctors and how that might affect their prescription behavior. My hypothesis is that more ethical perception can result into better doctors' response.   I used a likert scale of 5 points to identify both "the perception" and "the response" for each activity.  How can I analyze? What tool can better answer my question? should I analysis each activity separately or is there a tool to consider all of them as a whole?
7151
I have some  gained from survey questions.  In my case they are  responses (Strongly Disagree-Disagree-Neutral-Agree-Strongly Agree).  In my data they are coded as 1-5.  I  don't think means would mean much here, so what basic summary statistics are considered usefull?
60707
Take the case of book ratings on a website. Book A is rated by 10,000 people with an average rating of 4.25 and the variance $\sigma = 0.5$. Similarly Book B is rated by 100 people and has a rating of 4.5 with $\sigma = 0.25$.   Now because of the large sample size of Book A the 'mean stabilized' to 4.25. Now for 100 people, it may be that if more people read Book B the mean rating may fall to 4 or 4.25.   how should one interpret the comparison of means from different samples and what are the best conclusions one can/should draw?    For example - can we really say Book B is better than Book A.
41814
In my experiment, I asked 50 participants to rank on a 5 point scale which voice they preferred. I summed each particpants' rating for each voice: the total for voice 1 is 95, the total for voice 2 is 186.  Am I correct in doing this? Or should I analyse the raw data?  Which test should I use for this data? Would a t-test work here? Alternatively I thought I could use a chi-square test.   I am interested in seeing if the preference for voice 2 is significant.
28077
I need some advice regarding two main dilemmas in my research, which is a case study of 3 big pharmaceuticals and innovation. Number of patents per year is the dependent variable.  My questions are    What are the most important criteria for a good model? What is more/less important? Is it that most or all of the variables will be significant? Is it the prob of "F STATISTIC"? Is it the value of "Adjusted R squared"? Second, how can I decide the most appropriate model for the research? Besides patents which are a count variable (so maybe a Poisson count) I have explanatory variables such as return on assets, research and development budget, repeated partner (% not a binary variable), company size (employees) and a couple more. Should I do a linear regression or Poisson?
108625
I have a survey problem where the dependent variable (ordinal) is in Likert-type scale (i.e. 1 to 5 from most satisfied to most dissatisfied) and two sets of independent variables. One set has 7 IVs (almost the same scale but 1-5 scale) and a set of 5 IVs with a scale of 1-6, both ordinal. See   Which is the best way to analyze this kind of problem ? Do I need to treat the IVs as factors or covariates?
122437
I have some survey response data that are inconsistent and I'm not sure what is the best way to handle them.  This is the nature of the inconsistency:    Have you ever had a food poisoning episode that you think might have been caused by the food in a particular restaurant ? a) Yes b) No Did any of these episodes prevent you from eating at that restaurant again?  a) Does not apply, never have had a food poisoning episode b) Yes c) No Following these episodes, did you come back to your normal condition after 24 hours?  a) Does not apply, never have had a food poisoning episode b) Yes c) No   I believe that the intent of the designers of the survey was that anyone answering "No" to 1) should answer "Does not apply" to 2) and 3), but that's not how it worked. A large group of respondents picked "No" for 1) and "No" for at least one of 2) or 3).    What is the best way to deal with this inconsistency?    Where are some good references (books, papers, websites, etc.) to look at discussions and solutions for issues of this kind, and data cleaning in general?
114218
Today I came across an OBVIOUSLY good answer in /review. It had 7 upvotes, contained lists, paragraphs of explanation, and well-applied sample code. It was also moderately long. How does a question like this get flagged for review? I don't really know how the algorithm works.   If this is low-quality then I feel bad about all of my answers.  Here's a  if you care to see it in context. It's not really a huge problem (as Bart's comment emphasizes), but this seems like an extreme outlier in every measurable aspect.
75914
I find it hard to understand what really is the issue with multiple comparisons.  With a simple analogy, it is said that a person who will make many decisions will make many mistakes. So very conservative precaution is applied, like Bonferroni correction, so as to make the probability that, this person will make any mistake at all, as low as possible.   But why do we care about whether the person has made any mistake at all among all decisions he/she has made, rather than the percentage of the wrong decisions?    Let me try to explain what confuses me with another analogy.  Suppose there are two judges, one is 60 years old, and the other is 20 years old.  Then Bonferroni correction tells the one which is 20 years old to be as conservative as possible, in deciding for execution, because he  will work for many more years as a judge, will make many more decisions, so he has to be careful.  But the one at 60 years old will possibly retire soon, will make fewer decisions, so he can be more careless compared to the other.  But actually, both judges should be equally careful or conservative, regardless of the total number of decisions they will make.  I think this analogy more or less translates to the real problems where Bonferroni correction is applied, which I find counterintuitive.
2116
One of my students is an escort/stripper and she has offered me (and other faculty in my department) her "services". I am pretty sure my initial reaction of "thanks for letting me know, now can you answer the question about how to calculate the standard deviation", may not have been the best reaction. The offers have continued. My head of school is aware of the issue, and has asked if I want him to do anything.  Is the student doing anything wrong by offering her services to me? For what it is worth, prostitution is legal in the UK. Is this any different then a student telling me she works in a restaurant?  What is the correct response in a situation like this?
19341
The study I am analysing is a pre-and-post intervention questionnaire of students' views before and after studying a module.  The questionnaire was distributed in three different geographical locations, where the same instructor was delivering the same module at different times within one year.  The scale used is a 5-point Likert scale (which I can also convert into a binary agree/disagree variable if needed).   The surveys are anonymous, so I can't match the sample.  However, in some samples, all the students answered both the pre-and-post questionnaires (same $N$) and in others this was different (different $N$).   Overall I have 343 respondents for the pre-intervention questionnaire, and 378 respondents for the post-intervention questionnaire.  However in two of the three locations, I have equal pre and post intervention responses, but they are anonymous: so they are not independent, but not matched. (This is a weakness of the data, and will be reported in the results).  My questions are: a) Given the sample size, would running an unpaired t-test on the full sample be appropriate? Or should I be going for a non-parametric test?  b) Can the subsamples where there are equal respondents (i.e. all students answered both pre-and-post questionnaires) be analysed as non-independent non-matched samples?
91250
I am six years into a business role and have a bachelor's in physics and applied math/stats. Sean Carroll's (Caltech physicist)  opened me to the idea that Bayesian statistics is one useful way of thinking about anything - inevitably you hold a prior and you should update your credence as additional information becomes available.   Is there a path to training your intuition to thinking this way? Critically, it would require repeated practice with verifiable answers through either a course, or self study that includes many problems and solutions. I do not believe simply reading will do.  Possible resources, having read every related question on this site I could find:   "Probability Theory" by Jaynes. Pro: analytic; intuitive explanation of bayesian statistics. Con: prerequisites; missing problems/solutions. "Doing Bayesian Data Analysis" by Kruschke. Pro: includes problems &amp; solutions; requires only "algebra and rusty calculus". Con: works in R, which I think provides for less intuitive learning than the analytical (I may be wrong).   If it is a multi-year path I need to take, starting elsewhere, I am happy to do so! Ideally, I would avoid the frequentist methods, as I have no use for them.  My goal is not to be a scientist, but to leverage insight into how reality works to go above and beyond the established thinking in business.  Many thanks for any suggestions!
52973
I am currently writing 2 conference papers. One is highly quantitative in nature and the other is absolutely qualitative in nature. I am submitting both papers to conferences having deadlines in the next couple of months.  The papers present results on 3 different research questions on the same topic and are highly related with each other. You could argue that paper A + paper B together present a holistic view of the answer to these research questions. Individually, paper A and paper B show a different side to the problem since you generally get alternate points of view from quantitative and qualitative works.   Since the papers and their results are highly interrelated, there exists a compelling reason for me to ensure that they cite each other. I have seen  question and  question which are also highly related to my question. However, my question is different enough, in my opinion to warrant a separate question.    How should I cite these papers? (one paper is going to be in APA style and the other will be in ACM style) Does it make good sense to contact the Associate Chairs of these conferences for further clarification? The most important question for me is, is this ethical? Does it not break the double blind review system? I am ready to not cite these papers if that is the case.   I am having conversations with my adviser about this but just want some broader perspective from different disciplines if I am somehow missing something.
26100
I have a significant three-way interaction (with no significant two-way interactions and no significant main effects).  To begin with I have followed this up with two two-way ANOVAs (one at each level of the third variable). The first part of my question is whether this is an appropriate follow-up.  This showed no significant main effects or interactions at either level of the third variable...is this the end of the analysis?  If so, how would I interpret the three-way interaction?
14023
This question has been asked several times in similar (yet often slightly different) ways.  The general consensus seems to be that it's best to ask multiple questions individually in multiple Question posts so that each can be addressed separately. This is as it should be...in general (and in theory!). See related posts for some context and discussion:        In practice, however, it can be more useful to ask a few similar questions if they work together to express a single fundamental concern.   I propose that there are some situations when it is best to ask several questions together, rather than in multiple posts.  For example, sometimes the question-asker finds it difficult to ask something in one question and instead asks it in two or three similar questions to "beat around the bush". This often helps the poster express their fundamental concern more clearly or thoroughly and helps the community understand what the poster is thinking, and why.   Here are a few examples of multiple questions used effectively in a single post:        In these examples, answering one of the questions almost requires answering one of the accompanying questions as well. For this reason, it's better for all if the questioner and answerer each ask and answer these related questions together. Importantly, it also makes the question a much better resource for somebody who stumbles on that that question later, or has a similar question. As pointed out in , asking a cluster of questions can help distinguish one question from a near-duplicate and avoid an incorrect flagging as a duplicate.  In other cases (such as ), it's probably best to split the questions into multiple posts, but the end result can be a highly-useful repository of knowledge that is a "one-stop-shop".   I'm not satisfied with some SX users demanding separate posts for similar questions if the questions are essentially expressing the same concern. I'm also not satisfied with the prevalence of posts with multiple, disparate questions.   My question is this:    When is it okay to post multiple questions?  How can we distinguish between multiple questions that ought to be split vs. multiple questions that work together to express a single fundamental concern?  What guidelines or standards can we give and enforce for the community?    This is different than the related posts I've seen because I'm looking for guidelines. Whereas  was asking about how the user should frame his questions in the future, I'm asking what the SX guidelines should be.
78265
Few days back while attending a thesis defense, one Professor was asking the defender why does he think, he deserves the degree. I was wondering since then, is there really any general answer for that? or the answer should be given describing my own work and then emphasis them how it is important for research field?  I asked the question here to know your opinion about it and to list down what could be the possible answers to this question.
51831
Reading the question posted  left me with a more general question:  Given the professional title and name: Dr. (First Name)(Last Name), is there some way to differentiate between the holder of a philosophical doctorate and a medical doctor? Wouldn't it be more appropriate for a PhD holder to have the title (First Name)(Last Name), PhD?
42896
I read with interest  and the comment . I also read  and  the infamous FAQ answer   With rare exceptions, such as , the MSO attitude seems to be that people responding to questions have a "right" to choose not to directly answer the question in favor of an answer which basically tells the OP they "shouldn't be doing it that way". The advice all focuses on the information the OP should provide to avoid this kind of response rather than suggesting that those providing answers should be respectful of questions and not make assumptions that there is some underlying problem that the OP is trying to solve that should be addressed instead.  In rationalizing the approach of not answering the question, two "carpenter" analogies were used, one involving a question about how to cut balsa wood and the other involving a question which of two non-tool household items is better to pound a nail. In both cases, they ask the rhetorical question of whether it's better to answer the question or challenge the question.  My MSO question here is: Why do so many seem to think they have to choose between these two ways of responding? Why don't folks consider answering the question and supplementing their answer as they wish with questions, challenges, additional information, editorial opinion, etc. Not only is that more respectful to the OP, it's more respectful to future readers who arrived at the answer based on the question asked. If I do a search about how to cut balsa wood, I don't want to land on an answer that just tells me what a bad idea it is to use balsa wood in house construction.  Update: While I don't want to focus on specific examples, in response to some of the answers/comments, here's a recent one where I was the one asking the question:      Although it would take me a while to uncover examples, the more common occurrences I run into are where someone shares some code and an error they are getting and ask why they are getting that error. Instead of explaining the error, the answers typically propose some other approach. Admittedly, the OP is often times satisfied with that answer and not knowing why the error occurred, but I would contend the community is the poorer for it and, as a rule, this practice unnecessarily runs the risk of offending.