What are some examples of explanatory research questions?

The goal of explanatory research is to understand why something happens. This is often done by exploring a cause-and-effect relationship between two variables.

Examples of explanatory research questions include the following:

Does talking to plants (cause) make them grow faster (effect)?
Are people more likely to buy chocolate (effect) when they’re sad (cause)?
Does listening to music while studying (cause) improve students’ exam performance (effect)?

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Research: Other interesting questions

What is proportionate stratified sampling?: Proportionate sampling in stratified sampling is a technique where the sample size from each stratum is proportional to the size of that stratum in the overall population.

This ensures that each stratum is represented in the sample in the same proportion as it is in the population, representing the population’s overall structure and diversity in the sample.

For example, the population you’re investigating consists of approximately 60% women, 30% men, and 10% people with a different gender identity. With proportionate sampling, your sample would have a similar distribution instead of equal parts.
What is the difference between construct validity and internal validity?: Construct validity refers to the extent to which a study measures the underlying concept or construct that it is supposed to measure.

Internal validity refers to the extent to which observed changes in the dependent variable are caused by the manipulation of the independent variable rather than other factors, such as extraneous variables or research biases.

Construct validity vs. internal validity example
You’re studying the effect of exercise on happiness levels.

Construct validity would ask whether your measures of exercise and happiness levels accurately reflect the underlying concepts of physical activity and emotional state.

Internal validity would ask whether your study’s results are due to the exercise itself, or if some other factor (e.g., changes in diet or stress levels) might be causing changes in happiness levels.
What is a research design?: The research design is the backbone of your research project. It includes research objectives, the types of sources you will consult (i.e., primary vs secondary), data collection methods, and data analysis techniques.

A thorough and well-executed research design can facilitate your research and act as a guide throughout both the research process and the thesis or dissertation writing process.
What is a good inter-rater reliability score?: A good inter-rater reliability score depends on the statistic used and the context of the study.

For Cohen’s kappa (two raters), common guidelines are:

< 0.20: Poor agreement

0.21–0.40: Fair agreement

0.41–0.60: Moderate agreement

0.61–0.80: Substantial agreement

0.81–1.00: Almost perfect agreement

For the Intraclass Correlation Coefficient (interval or ratio data), similar thresholds are used:

< 0.50: Poor agreement

0.51–0.75: Moderate agreement

0.76–0.90: Good agreement

> 0.91: Excellent agreement
Is ordinal data qualitative or quantitative?: Ordinal data is usually considered qualitative in nature. The data can be numerical, but the differences between categories are not equal or meaningful. This means you can’t use them to calculate measures of central tendency (e.g., mean) or variability (e.g., standard deviation).