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According to Dictonary.com, “haze” in the verb form can mean to subject freshmen, newcomer, etc. to abusive and humiliating tricks and ridicule. It has a French origin from the word “haser,” which means to annoy or to irritate. Traditionally, potential inductees to college fraternities and sororities have been subjected to hazing. Anderson (2015) for instance, writes, “Once, for hazing, had to chug a concotion [sic] of blended locusts, hearts, lungs, bananas and poo, human poo.” There is a plethora of information on academic hazing available on the Internet. A search on Google yielded 443,000 hits. For instance, academic hazing can occur when professors attempt to get tenure (Hiatt, 2008). There is another form of academic hazing that I have become aware of as a freelance statistics consultant providing help with statistics to doctoral candidates, and that is the academic hazing of doctoral candidates. Before I explain further, I think it’s necessary to put this in perspective. Usually, when a doctoral student is admitted into candidacy, they have already passed their doctoral comprehensive exams and the admission to candidacy is a formal acknowledgement and approval that the candidate can officially begin work on the dissertation. Even admission to a doctoral program is quite an accomplishment and at that level, the doctoral student is often considered an equal to faculty; at least in some aspects. Academic hazing at the doctoral level may not occur to the extremes as some of the worst case scenarios like the one previously cited, but it seems to fit the definition, at least in my opinion. There are two areas wherein I’ve observed that doctoral candidates get hazed; a) not providing timely feedback and b) requiring revisions that were not previously mentioned during the appropriate phase of the process or timeframe. Dissertation reviewers often take too long to provide feedback. To make matters worse, they take weeks to respond to simple questions that should take them less than five minutes to answer. I actually did a research project on timely feedback. Schools have deadlines for faculty in providing timely feedback, but there are no consequences to faculty when they ignore the deadlines. When deadlines are ignored, this results in increased tuition costs for the candidate because it unnecessarily delays their progression through the dissertation stage, which causes mental anguish. Another method of academic hazing at the doctoral level occurs after doctoral candidates have been given approvals, but then those approvals are later rescinded because some revisions are now required. When I was a doctoral student, I completed a dissertation proposal. Once the proposal was approved, I could collect my data. The dissertation proposal is a contract between the student and the school. This “contract” details what analyses will be done to answer the research questions. Sometimes, however, after the candidate collects the data and the data has been analyzed and Chapter 4 (results chapter) has been completed, candidates are required to make changes to the research questions and/or hypotheses. These types of issues should be resolved BEFORE the proposal is approved. In some schools, requiring a candidate to make changes to research questions after proposal approval would not be allowed. Another related scenario occurs when a candidate is required to make other revisions. Making revisions is not solely the issue of concern. Even articles submitted for the peer review process are rarely accepted on the first submission and usually require revisions before acceptance for publication. I’m referencing something more insidious. Let’s say, for example, a candidate submits a dissertation with Sections A, B, and C for review. The reviewer returns Section C for revisions. The candidate makes all the required revisions to Section C. Then the reviewer finds issues with Section A. Why weren’t the problems with Section A mentioned when Section C was returned to the candidate for revisions? I can surely understand the frustration that doctoral candidates experience when subjected to this type of maltreatment. I’ve been providing statistics assistance to doctoral candidates working on their quantitative dissertations for 10 years and during the past 10 years, I’ve learned a lot about the politics of the doctoral process. Here are six options you can pursue if you believe you are being hazed or if you are being treated unfairly by your dissertation reviewers. Some of the following suggestions are simply good practices even if you are not being hazed. 1) The first thing you can do is ask for your Dissertation Chair or mentor to advocate on your behalf. That’s one of their roles. 2) You might also consider discussing the possibility of the committee member being a co-author for a publication related to your dissertation. This discussion may change the nature of your relationship for the better. 3) Another suggestion is to make sure you request all recommended and required changes in writing. This will help hold your reviewers more accountable for their requirements. 4) When sending emails, also send carbon copies of the emails to others who have a vested interest in your success. Often, this is your doctoral committee members. 5) Another option to consider is discussing the situation with your student advisor. 6) If none of the previous suggestions are effective, as a last resort, you can request that your Dissertation Chair, mentor, or committee member be replaced. The doctoral degree is an elitist degree. If it were easy, everyone would have one. Just because candidates become part of an exclusive club does not give the gatekeepers the right to subject them to maltreatment as a condition of acceptance. Academic hazing is about power and control and has nothing to do with teaching scholars how to be competent researchers. References Anderson, C. (2015). A bunch of frat daddies shared their worst, most gruesome hazing stories with us and good God. Retrieved from http://brobible.com/college/article/worst-fraternity-hazing-stories-brobible-reader-submissions/ Hiatt, G. (2008). Bullying of academics in higher education. Retrieved from http://bulliedacademics.blogspot.com/2008/02/mean-and-nasty-academics-bullying.html

I recently solicited topics on social media for me to write about, and someone suggested the above topic. She wanted to know how to develop research questions that produce optimal results in SPSS, and this is my rationale for the current article. In quantitative studies, there are two main categories of statistical tests and therefore there are two main categories of research questions formulated that require the types of tests; tests of differences or tests of similarities. Quantitative research questions can also be descriptive, but descriptive research questions are usually considered to be of insufficient rigor for a dissertation. By “tests of differences,” I am referring to mean differences between groups based on some dependent variable. Such research questions should begin with “Is there a significant difference…?” The prevalent wisdom in this area, however, is that research questions should not be formulated in a manner that can be answered with a simple “yes,” or simple “no.” Therefore, in the previous example, an alternative way of formulating the question is, “To what extent is there a difference…?” The other category of statistical tests is associated with similarities and by similarities, I am specifically referring to correlation or regression. Regression is an advanced correlational technique. These research questions should begin as follows: “Is there a relationship between…?” Following the previous format, an alternative way of asking the research question is as follows: “To what extent is there a relationship between…?” Implicitly, the researcher should pay attention to the language used to formulate the research questions. The language used implies (or at least should imply) a specific statistical approach. The word “difference” suggests testing for mean group differences and the word “relationship,” implies correlation or regression. Sometimes candidates mix the languages of the two different approaches and this is the reason that their proposals do not get approved. When the language is mixed, confusion about the appropriate statistical test is a logical consequence. Now that I’ve discussed the two main types of research questions, I shall discuss more about the nature of the questions. It goes without saying that a research question should be testable. When I was a doctoral student, I recall reading an example of a hypothesis that cannot be tested. It was, “All republicans go to heaven.” I laughed when I first heard this, but it makes the point. This cannot be tested empirically; at least not on this side of eternity (LOL). I’ve read some research questions that on the surface appear to be testable, but when I look further into the proposal, the variables mentioned in the research question are not being tested. The researcher must be able to operationalize every variable mentioned in the research question. Research questions must also be clear and concise. There may be several eyes reviewing the research questions as they are being developed, and reviewers often make recommendations about what to include, but the researcher needs to stay focused on the goal of the research question and not get off the path by scope creep or trying to satisfy all reviewers’ suggestions with one research question. It is often the case that these research questions can be broken down into two or more questions in order to include the relevant information. Research questions must be free from bias and hidden agendas. When I see research questions that violate this principle, I imagine someone being on a witness stand and being asked leading questions by an attorney. Here’s an example of such a research question: “To what extent is there a relationship between self-esteem and depression among females who should be incarcerated for their lack of parenting skills?” Reflecting on my own experiences, students may become aware of their inherent biases during their master’s degree programs, so one would not expect to see these types of research questions from doctoral students. However, they still occur. Another related approach I’ve seen is that doctoral candidates formulate research questions with a secondary statement assumed to be true, but that can (and should) also be tested. In this brief article I’ve attempted to provide a basic foundation for the doctoral candidate in developing the quantitative research question. I sincerely hope that I have not oversimplified this process. This can be quite confusing because sometimes statistical tests can be classified into either category; tests of differences or tests of similarities or association. The chi-square test of independence is one example. In this instance, it depends on the wording of the research question, and the scales of measurement of the data being tested. Producing optimal results in SPSS require more than well-developed research questions. They also require a well-developed data analysis plan, but that’s a subject for another article. In hindsight, I should have asked the requester what she meant by “optimal.”

Data analysis is often a daunting task for doctoral candidates, and mistakes can lead to invalid results. In this blog, we’ll highlight common pitfalls in data analysis and offer tips to avoid them.

A clear and testable hypothesis is the foundation of any successful dissertation. In this blog, we explore why a well-formulated hypothesis is crucial and how it sets the direction for your entire study.

Selecting the appropriate statistical test can be one of the most confusing parts of a dissertation. In this blog, we’ll guide you through the process of choosing the right test based on your research goals, data type, and hypothesis.