Nature and meaning of science

A controlled experiment isolates the independent variable to test causation. Distinguish correlation from causation.

A third factor may create a misleading relationship so it is a confounding variable. Identify hidden influencing factors.

Planning in advance increases transparency and prevents changing the story to fit results. Link it with research integrity.

Extraordinary claims require evidence of high quality and strength. Match the strength of evidence to the claim.

Simplicity is not a substitute for evidence but reduces unnecessary assumptions. Choose an adequate and simple explanation.

A numerical difference should also be judged for real-life importance. Do not conclude from statistical difference alone.

Removing data requires a clear scientific reason and documentation. Identify data transparency.

Direct answer: Option A, other researchers can independently verify the analysis. Raw data means the original measurements or recorded observations collected during the investigation, before they are summarised or interpreted. When researchers share these data, another researcher can repeat the calculations, check whether the values were entered correctly, look for unusual values, and use a different suitable method of analysis. Step by step: the scientist collects observations; records them; shares the unprocessed records; another researcher examines them independently; and agreement or disagreement can then be discussed using evidence. Option A is correct because it gives transparency and allows checking. Option B is wrong because sharing data does not make a conclusion automatically correct; the data may still be poor or interpreted incorrectly. Option C is wrong because sharing data may reveal bias, but it cannot make all bias disappear. Option D is wrong because data sharing cannot replace doing the experiment and collecting evidence. Memory cue: raw data means “show the original evidence so others can check.”

Constructive criticism helps improve studies and strengthen conclusions. Link criticism with review.

Changing the explanation after every result can make a claim effectively untestable. Look for clear prior predictions.

A very small change may be hidden within measurement uncertainty. Consider experimental sensitivity.

Without a control group other causes and expectation effects cannot be separated. Be cautious when claiming causation.

An unsupported hypothesis can clarify limits and guide new investigation. Link failure with learning.

Stating uncertainty clarifies the strength and limits of a conclusion. Treat it as scientific honesty.

The direct answer is A: research ethics. In a study involving people, asking for informed consent means explaining the study sufficiently and allowing participants to choose freely whether to take part. This protects their autonomy, dignity, privacy, and safety. Step by step: identify that human participants are involved; explain the purpose, procedures, possible benefits, and risks in understandable language; allow questions; make sure participation is voluntary; obtain consent before collecting data; protect personal information and allow withdrawal where appropriate. Option A is correct because consent is a basic requirement of ethical research involving human beings. Option B, “measurement precision,” concerns how closely repeated measurements agree; it does not concern permission or participant rights. Option C, “sample size,” means the number of participants or observations; a large sample still requires consent. Option D, “scientific law,” is a well-supported general relationship in nature, not a rule about treating participants. Consent is especially important because researchers have responsibility toward people who provide information or undergo procedures. Memory cue: people are participants, not merely data; ask permission and protect their rights.

Competing explanations should be separated by testing their different predictions. Identify a decisive test.

A clear method is necessary for repetition and independent verification. Understand the importance of scientific communication.

A scientific prediction arises from evidence and known relationships. Distinguish it from an unsupported guess.

Selecting only supporting evidence is confirmation bias. Choose balanced evaluation of all relevant evidence.

External validity concerns generalising results. Examine similarities in samples and conditions.

Scientific knowledge is strengthened through review collaboration and independent checking. Understand science as a social process.

Improving a model according to new evidence is a strength of science not a weakness. Link revision with progress.

A balanced conclusion requires evaluation of both benefits and risks. Identify incomplete reporting.

Science includes both knowledge and the processes of inquiry review revision and communication. Treat science as both knowledge and process.

Without a clear measurement method it is difficult to assess data quality and repeat the study. Link transparent methodology with reliable science.