How to formulate research questions and hypotheses?
Research questions organize the entire study. The selection of the sample, tool, data and method of analysis depends on them. Hypotheses, however, are not guesses at the outcome, but justified guesses that can be verified. Well-formulated, they protect the work against the collection of information that will later be of no use.
Key information
- ✓The main problem should result directly from the purpose of the work.
- ✓Detailed questions break the problem down into researchable parts.
- ✓The hypothesis indicates the predicted relationship and must be verifiable.
- ✓Each question must be linked to specific data and a method of analysis.
From the goal to the main problem
If the goal is to assess the impact of remote work on employee satisfaction, the main problem should concern this relationship. It cannot suddenly cover all aspects of human resource management.
A good question is unambiguous, limited to a specific population or context, and answerable. Avoid questions that can only be answered with "yes" or "no" if you need in-depth analysis.
Detailed questions without repetitions
Detailed questions break down the problem into specific dimensions. They may concern the frequency of the phenomenon, differences between groups, respondents' opinions or the relationship between variables. Together they should lead to the answer to the main question.
Read the questions side by side and remove those that mean almost the same thing. Also check that each has its place in the research tool and the subsequent results chapter.
How to build a hypothesis?
The hypothesis should specify the predicted relationship, difference, or direction of change. Instead of writing "remote work affects employees", indicate which feature of remote work is related to which dimension of the functioning of a specific group.
The justification for the hypothesis comes from the literature, previous research, or a theoretical model. Intuition can spark an idea, but in scientific work you need to show the basis for prediction.
Variables and method of measurement
A variable is a feature that takes on different values, for example age, stress level or frequency of using the service. It must be determined how it will be recognized or measured in a specific study.
General concepts require operationalization. If you're analyzing engagement, identify the survey questions, scale, or observable metrics that will represent it. Without this, hypotheses remain declarations.
Inspection before starting the test
For each question, write down the data source, unit of analysis, and planned technique for developing the results. This simple spreadsheet quickly reveals questions that are too general or for which the tool doesn't collect the necessary information.
Finally, check the problems' consistency with the title, goal, theory and method. Changing one of these elements often requires correcting the others, so it is worth checking it before distributing the survey or conducting interviews.
Summary
Research questions are useful when they lead to specific methodological decisions and can be answered based on the data collected. Hypotheses should result from theory, indicate the predicted relationship and be subject to verification. Before you start the study, check each question together with the planned analysis method. If it is not clear what answer to look for in the data, the wording needs to be clarified.
Frequently asked questions
Does every work have to contain hypotheses?
NO. The hypotheses are typical of explanatory and quantitative research. In exploratory or qualitative research, well-formulated research questions may be sufficient.
How many research questions should be included in the paper?
There is no universal number. Usually one main question develops into several detailed questions. Each of them should be necessary and analysable.
Can the hypothesis not be confirmed?
Yes. The rejection of a hypothesis is a legitimate result of the study. Don't change data or wording after analysis just to get confirmation.
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