What Is P-Hacking? Imagine you run a study and your result comes back with a p-value of 0.08 — just above the usual 0.05 cut-off for “statistical significance.” Nothing is significant, and your hypothesis looks unsupported. So you try a few things: you drop a couple of unusual responses, you test a different subgroup, you …
Introduction You have spent weeks designing your questionnaire. The questions look clear to you, the order feels logical, and the response scales seem obvious. Then you send it out to 300 people — and the problems start pouring in. Respondents email you to ask what a question means. Half of them abandon the survey halfway …
Why Most Literature Reviews Read Like a Shopping List If you have ever read a literature review that goes “Smith (2020) found X. Jones (2021) found Y. Lee (2022) found Z,” you already know the problem. Study after study is lined up in a row, each described on its own, and the reader is left …
Every hypothesis test is a decision — and like every decision, it can be wrong in two different ways. Understanding type 1 and type 2 errors matters because these two mistakes shape how you design a study, choose your sample size, and interpret a p-value. The idea is simple once you see it clearly. A …
If you have ever filled in a questionnaire that asked you to rate statements from “Strongly disagree” to “Strongly agree”, you have already used a Likert scale. It is the most common way researchers measure attitudes, opinions and perceptions — and yet it is also one of the most commonly mishandled parts of a student …
Introduction If you have ever sat in front of twenty open PDFs, a half-written literature review, and the sinking feeling that you have read everything but remember nothing, you are not alone. That is the moment most students discover they needed a system — not more reading. A literature review matrix is that system. It …
You have just run your analysis, and there it is: p = .03. Significant! Time to celebrate? Not so fast. That p-value tells you your result is unlikely to be pure chance — but almost nothing about whether the difference actually matters. A tiny, meaningless difference can be “significant” with a big enough sample, and …
Imagine you run a survey to find out whether students like your university’s new online library. You ask: “Don’t you agree that the new online library is a huge improvement?” Most people say yes — and you walk away thinking the library is a hit. But did you actually measure their opinion, or did your …
If your supervisor has just asked you for an annotated bibliography and your first thought was, “Is that just a reference list with extra steps?” — you are not alone, and you are not far wrong. An annotated bibliography is a list of sources, but each entry carries a short paragraph that shows you actually …
What Is Power Analysis? Imagine you run a study comparing two teaching methods. You collect data from 20 students, run your test, and get a non-significant result. Does that mean the two methods work equally well? Not necessarily — your study may simply have been too small to detect a real difference. This is the …