Collecting Data and Experiments

Flashcards covering key concepts from the lecture notes on collecting data, sampling methods, biases, and experimental design.

Population

Entire group of interest.

Sample

Subset of the population.

Census

Data from every individual in the population.

Simple Random Sample (SRS)

Everyone has an equal chance of being selected.

Stratified Sampling

Divide the population into groups (strata), then take SRS from each.

Cluster Sampling

Divide the population into clusters (mini-populations), select SRS of clusters and sample all individuals in chosen clusters.

Systematic Sampling

Pick a random start and then select every nth individual.

Convenience Sample

A sample that is easy to reach, often leading to bias.

Voluntary Response Sample

A sample where individuals choose to participate, typically biased.

Bias

When a study consistently overestimates or underestimates a population parameter.

Undercoverage

Occurs when some groups are missed in the sampling frame.

Nonresponse

When selected individuals do not respond to surveys or sampling.

Response Bias

When responses are affected by leading questions or social desirability.

Observational Study

A study where researchers observe without intervening; cannot show causation.

Experiment

A study where variables are manipulated to observe effects; can show causation.

Experimental Units/Subjects

The individuals or items being tested in an experiment.

Treatment

The condition applied in an experiment.

Factor

Independent variable in an experiment (e.g., dosage).

Levels

Specific values of a factor (e.g., low/high dose).

Control Group

Group that receives no treatment or a placebo for comparison.

Placebo

A fake treatment used as a control in experiments.

Random Assignment

A method to create comparable groups in an experiment.

Control

Keeping other factors constant in an experiment.

Replication

Using enough subjects in an experiment to detect an effect.

Blinding

A method where subjects and/or researchers do not know which group individuals are assigned to.

Confounding

When another variable influences the dependent variable.

Explanatory Variable (x)

The variable that predicts change.

Response Variable (y)

The variable that measures the outcome.