Inferential statistics are powerful tools for uncovering patterns and testing relationships. But they are also easily misused. One of the most frequent and damaging mistakes we see at Research & Report Consulting is treating correlation as causation. This statistical misstep is more than a technical flaw—it undermines credibility, damages publication chances, and can lead to … Read more
In qualitative research, validity is not merely technical — it is deeply interpretive, ethical, and relational. Yet, while researchers meticulously detail methods, tools, and coding frameworks, they often gloss over or omit a critical component: positionality and reflexivity. This oversight undermines not only the credibility of the study but also its epistemological integrity. At Research … Read more
Time-series models are among the most powerful tools in empirical research — used to forecast trends, evaluate policy impacts, and assess long-term relationships across economics, finance, climate, and public policy. But too often, researchers focus on sophisticated modeling techniques (like ARDL, VAR, or VECM) without laying the proper statistical foundation.The result? Spurious regressions, invalid inferences, … Read more
In quantitative research, justifying sample size is a fundamental requirement. Yet, one of the most misused tools in this process is G*Power — a free and powerful program that helps estimate sample sizes based on power analysis.While G*Power is valuable, it’s often misapplied or overly relied upon, leading to flawed research designs, underpowered studies, and … Read more
Despite the growing acceptance and institutionalization of qualitative research in academia, many studies still fall into a critical trap — they lack a solid theoretical foundation. While qualitative methods are celebrated for exploring complexity, meaning, and lived experience, they are increasingly being used in ways that are conceptually shallow, methodologically misaligned, and analytically weak. This … Read more
Regression analysis is one of the most widely used statistical tools in empirical research. Yet, beneath many published models lies a silent killer of validity: the misuse of control variables. Too often, researchers include controls reflexively — without a clear understanding of their role in causal inference or model integrity. This article dives into what … Read more
