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A worthwhile research question can still become an impossible study. Learn how to test your idea against participants, data, time, money, expertise, ethics, and practical constraints before you commit.
Read Guide →A small or hard-to-reach population does not automatically make a study impossible. Learn how to distinguish rarity from inaccessibility and adapt your sampling, recruitment, scope, and claims accordingly.
Read Guide →Finding a dataset with the variables you need is only the beginning. Learn how to evaluate its design, population, measures, quality, missingness, documentation, access conditions, and analytical fit before building your study around it.
Read Guide →A dataset can contain the variables and cases you need yet still represent the wrong population. Learn how to compare the population implied by your research question with the population the dataset can actually support.
Read Guide →Not every worthwhile research question can be answered with the data currently available. Learn when to adapt the study, seek different evidence, or stop rather than force a weak dataset to support a stronger conclusion than it can justify.
Read Guide →Specialists are most useful before difficult research decisions become irreversible. Learn when statistical, methodological, technical, or other expertise should enter your project and what to prepare before asking for help.
Read Guide →A research question can be important, original, and methodologically sound yet still be a poor thesis project if answering it properly costs more than you can realistically afford. Learn when to fund, redesign, narrow, or postpone it.
Read Guide →The ideal study may require more money than you have. Learn how to identify what is essential, compare lower-cost designs, narrow scope intelligently, and preserve the strongest research question your resources can support.
Read Guide →The strongest study on paper is not always the strongest study you should conduct. Learn how to distinguish necessary rigor from unnecessary ambition and design research that is both credible and realistically completable.
Read Guide →Simplifying a study can make it more focused, affordable, and achievable. But simplify too far and you may remove the evidence or significance that made the research worthwhile. Learn where to draw the line.
Read Guide →Some research ideas are worth pursuing but impossible under your current time, access, funding, skills, participants, or resources. Learn how to preserve the idea, identify what makes it infeasible, and build a realistic pathway toward studying it later.
Read Guide →An important research question should not automatically be abandoned because it requires an unfamiliar method. The real decision is whether you can develop the necessary competence, support, and time without compromising the study.
Read Guide →Research ethics should enter the conversation before your research question is finalized, not only when you prepare an ethics application. Early ethical thinking can reveal whether a worthwhile question can be investigated responsibly and whether the question itself needs refinement.
Read Guide →Ethical problems do not always require changing the research question. But when every acceptable method changes the evidence, population, construct, or inference needed to answer it, the ethical constraint has reached the question itself.
Read Guide →Every research study needs boundaries. Learn how to define what your study covers, justify what it deliberately excludes, and distinguish delimitations from limitations you cannot fully control.
Read Guide →A research scope should be narrow enough for the question to be answered rigorously with the available evidence, time, access, expertise, and resources, but not so narrow that the resulting question loses significance. The right scope is therefore a balance between feasibility and meaningful contribution.
Read Guide →A study may be trying to answer too much when its questions collectively require substantially different populations, evidence, methods, constructs, or analyses that cannot all be handled rigorously within one coherent and feasible design. The problem is not complexity itself, but whether the project can still produce convincing answers to its central question.
Read Guide →A delimitation is a boundary deliberately established by the researcher to define what a study will and will not investigate. A well-justified delimitation can strengthen a study by keeping its question, evidence, and claims coherent rather than attempting to cover every possibility.
Read Guide →Leave something out of a study when it is not necessary to answer the research question, falls outside the phenomenon or population of interest, or adds complexity without sufficient methodological value. Exclusion should sharpen the inquiry without removing evidence the study actually needs.
Read Guide →Excluding a population or variable can be methodologically justified when the exclusion follows from the research question, protects participants, improves measurement or comparability, or serves another defensible design purpose. The key question is what the exclusion does to the evidence and the conclusions you intend to draw.
Read Guide →Narrowing the scope can improve a study when it removes unnecessary complexity while preserving what is needed to answer the research question. The goal is not a smaller study for its own sake, but a more coherent match among the question, evidence, methods, and claims.
Read Guide →A research question becomes too narrow when its boundaries make the study manageable but remove so much uncertainty, variation, significance, or applicability that answering it contributes little. The goal is not maximum breadth, but a focused question whose answer still matters.
Read Guide →Consequential exclusions should usually be explained when readers need the rationale to understand or evaluate the study. The explanation should identify why the population or variable was excluded and what that decision means for the evidence and conclusions.
Read Guide →If available data cannot support the original scope, do not force them to answer a broader question than they can address. Determine what evidence the question actually requires, assess whether other data can provide it, and narrow or reformulate the question transparently when necessary.
Read Guide →One study begins to look like several when its questions require substantially independent populations, evidence, methods, analyses, or conceptual rationales and no longer need to be answered together. Related questions can belong to the same research program without being forced into a single study.
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