Flashcards on Types of Science, Pseudoscience, and the Scientific Method

Flashcards covering distinctions between science, pseudoscience, and nonscience; limitations and steps of the scientific method; deductive vs inductive inquiry; data types; experimental design (mouse models and LDL in breast cancer); and interpreting results (p-values, error bars, correlation vs no correlation).

What distinguishes science from pseudoscience and nonscience?

Science is based on data and repeatable evidence; pseudoscience and nonscience rely on anecdotes or claims without verifiable data.

What is a key limitation of science as new data emerges?

Conclusions are limited by the current data and can change as more data are collected.

What did an image-forensics database reveal about scientific papers?

Duplicate images across multiple papers, suggesting potential figure manipulation or reuse.

What is the initial step that the notes say is missing at the very top of the scientific method?

Observe something weird or interesting to generate questions.

What is a hypothesis and how should it relate to a question?

A hypothesis is a testable statement (not a question) designed to be tested to see if data support or reject it.

What is the role of data collection and analysis in evaluating a hypothesis?

Collect data, analyze them, and determine whether the results support or reject the hypothesis.

Why is sharing results with the scientific community important?

To obtain feedback, enable replication and critique, and let others build on the findings.

What does the note imply about discoveries built on prior work?

Every discovery is based on decades of research and many prior references.

What is deductive inquiry in the notes?

Starts from existing theory or observation and proceeds through hypothesis, data collection, analysis, to support or reject the hypothesis.

What is inductive inquiry in the notes?

Involves observations, correlation studies, surveys, and discovery-based approaches to generate generalizations.

What is the difference between qualitative and quantitative data?

Qualitative data describe qualities (non-numeric); quantitative data are numerical measurements.

What is a xenograft in cancer research?

Transplanting cells from one species into another (e.g., human breast cancer cells into mice).

What did the mouse model study test regarding LDL and breast cancer?

Whether a high LDL diet affects tumor growth in a breast cancer xenograft model.

What does LDL stand for and why is it mentioned in the notes?

Low-density lipoprotein; described as “bad cholesterol” linked to tumor growth in the example.

What is meant by a correlation study?

A study that looks for relationships between variables (often observational or survey-based) without proving causation.

What does 'no correlation' mean in data interpretation?

There is no consistent trend in the data in either direction.

Why should hypotheses be specific and testable, rather than vague questions like 'does garlic butter make you feel better'?

To be empirically testable with data; vague questions cannot be adequately tested.

What is the role of p-values in the notes, and how are they described?

A p-value < 0.05 is considered significant; the notes describe this as indicating high precision/accuracy.

Why might a graph lack error bars, and how should the data be treated?

Some data (e.g., percentages) make error bars hard to show; trust the data and rely on appropriate statistical tests when interpreting differences.

What is the main purpose of an experiment beyond simply spreading knowledge or obtaining funding?

To enable others to test, critique, and build on the work, advancing community understanding.