This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline. Library and Information Studies is especially suitable for…
Author: Zlatko Kovačić
Director of Wellington based My Statistical Consultant Ltd company. Retired Associate Professor in Statistics.
Has a PhD in Statistics and over 45 years experience as a university professor, consultant, international researcher and government advisor.
Information Technology Research by Design: Questions, Hypotheses, Data and Methods
This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline. Information Technology is especially suitable for this exercise…
When Conclusions Go Beyond the Evidence
Why responsible research depends not only on good data, but on interpretive restraint Opening: the final mistake often happens at the very end Some studies are well designed, carefully executed, and still weakened in the last few pages. The data may be real, the analysis…
Geography Research by Design: Questions, Hypotheses, Data and Methods
This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline. Geography is especially suitable for this kind of…
Agricultural Research by Design: Questions, Hypotheses, Data, and Methods
This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions (RQ), research hypotheses (RH) or working propositions, data (D), and methodology (M) can be aligned in one specific discipline. Agriculture…
When the Design Cannot Support Causal or Explanatory Claims
Why many studies promise explanation or causation even though their design can only describe or associate Opening: the problem is often not the result, but the claim One of the most persistent mistakes in empirical research is not that the data are fabricated, the analysis…
Biology Research by Design: Questions, Hypotheses, Data and Methods
This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline. Biology is especially well suited for this exercise…
Archaeology Research by Design: Questions, Hypotheses, Data and Methods
This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline. Archaeology is especially suitable for this exercise because…
When Mixed Methods Are Mixed in Name Only
Why using both qualitative and quantitative data is not enough if the study never truly integrates them Opening: having two strands is not the same as having one study A study does not become mixed methods merely because it contains both numbers and narratives. Researchers…
When Qualitative Evidence Is Too Thin
Why weak interviews, weak observation, and low analytic yield belong to the same research-design problem Opening: the transcript is long, but the evidence is still thin One of the most misunderstood problems in qualitative research is the belief that a large amount of material automatically…