Scientific Research Vocabulary in English

A hypothesis is a specific, testable prediction made before conducting research — for example, “increasing temperature will speed up the reaction.” A theory is a well-substantiated explanation supported by extensive evidence and repeated testing — for example, the theory of evolution. In everyday English, “theory” often means a guess, but in science it means the opposite: a strongly supported framework. This distinction is important for academic writing.

Correlation means two variables tend to change together — for example, ice cream sales and drowning rates both rise in summer. But this does not mean one causes the other (both are caused by hot weather). Causation means one variable directly causes changes in another. Establishing causation requires controlled experiments, not just observational data. The phrase “correlation does not imply causation” is one of the most important concepts in scientific literacy.

Peer review is the process by which a piece of scientific research is evaluated by other experts in the same field before it is published in an academic journal. Reviewers assess the validity of the methodology, the interpretation of data, and the significance of the findings. Peer review helps maintain standards in scientific publishing and is one of the reasons why peer-reviewed sources are considered more reliable than non-reviewed publications.

Quantitative research involves collecting numerical data and analysing it statistically — for example, measuring the blood pressure of 500 patients. Qualitative research involves collecting non-numerical data such as words, images, and opinions through interviews, observations, or focus groups. Both approaches are valid and often complementary. Mixed methods research combines both. The choice depends on the research question and what the researcher is trying to understand.

A double-blind trial is an experimental design where neither the participants nor the researchers know who is receiving the treatment (drug, intervention) and who is receiving the placebo. This eliminates both participant and researcher bias — the tendency for expectations to influence results. Double-blind randomised controlled trials (RCTs) are considered the gold standard in clinical research for testing the effectiveness of medical treatments.

A longitudinal study follows the same group of participants over an extended period of time — months, years, or even decades — to observe how certain variables change over time. For example, the UK Biobank study has tracked hundreds of thousands of participants over many years to understand how genetics, lifestyle, and environment affect health. Longitudinal studies can reveal long-term trends that cross-sectional studies (which take a snapshot at one point in time) cannot.

Empirical evidence is evidence gained through observation, experiment, or direct experience rather than through theory or reasoning alone. Science is an empirical enterprise — claims must be supported by observable, measurable data. “The drug reduced symptoms in 78% of patients” is empirical; “the drug should work because of this theory” is not. Empirical evidence is the foundation of the scientific method.

Replication is the repetition of an experiment by independent researchers to verify that the original results are reliable. If a study cannot be replicated, its findings are called into question. Science has faced a replication crisis in recent decades — many famous psychology and medical studies have failed to replicate when other labs tried to reproduce them. Replication is therefore a key element of scientific credibility.

Research bias is any systematic error in how a study is designed, conducted, or reported that causes the results to deviate from the truth. Types include selection bias (unrepresentative sample), confirmation bias (seeking evidence that supports a pre-existing belief), and publication bias (journals preferring positive results). Bias is reduced through randomisation, blinding, pre-registration of study protocols, and transparent reporting.

In an experiment, the independent variable is the factor the researcher deliberately changes or manipulates — for example, the dose of a medication. The dependent variable is what the researcher measures to see if it changes as a result — for example, the patient’s blood pressure. The hypothesis typically predicts the relationship between them: “Increasing the dose (independent variable) will reduce blood pressure (dependent variable).”