AP Statistics: Data Collection, Sampling, Bias, and Experimental Design

Comprehensive vocabulary flashcards covering statistical data collection methods, sampling techniques, forms of bias, and principles of experimental design.

Census

A data collection method that includes every member of a population.

Observational Study

A study that observes individuals and measures variables without imposing any treatments.

Experiment

A study that imposes treatments on experimental units to measure and investigate their effects.

Survey

A data collection method that asks questions to collect information from individuals.

Population

The entire large group of individuals or objects about which information is sought.

Sample

A subset of individuals selected from a population.

Experimental Unit

The individual or object receiving a treatment in an experiment.

Subject

An experimental unit that is a person.

Treatment

The specific condition imposed on experimental units in an experiment.

Explanatory Variable

The variable used to explain or predict an outcome.

Response Variable

The variable that measures the outcome of a study.

Random Selection

The process of randomly choosing individuals from a population, which helps generalize results to the population.

Random Assignment

The process of assigning experimental units to treatment groups by chance, which helps support cause-and-effect conclusions.

Association

A condition where two variables are linked, but one does not necessarily cause the other; observational studies can identify associations.

Causation

A relationship where one variable directly affects another; well-designed randomized experiments can provide evidence of causation.

Prospective Study

A study that follows individuals into the future to collect data.

Retrospective Study

A study that uses past records or asks individuals to recall past events.

Random Sampling

A selection process that relies on chance to determine who gets selected from a population.

Simple Random Sample (SRS)

A sampling method in which every possible sample of a given size has an equal chance of being selected.

Sampling Frame

The list or source from which a sample is drawn, such as an index card list with names.

Sampling Variability

The natural differences observed among multiple distinct samples drawn from the same population.

Stratified Random Sampling

A sampling method that divides the population into groups (strata) and takes random samples from every group.

Cluster Sampling

A sampling method that divides the population into clusters, randomly selects some clusters, and surveys everyone in those selected clusters.

Systematic Sampling

A sampling method that starts at a random point and selects every $n^{\text{th}}$ individual.

Sampling With Replacement

A sampling process where an item is drawn, noted, and put back in, meaning a selected individual can be selected again.

Sampling Without Replacement

A sampling process where an item is drawn and kept out, meaning a selected individual cannot be selected again.

Bias

A systematic tendency to produce results that differ from the truth; increasing sample size does not fix bias.

Voluntary Response Bias

A type of bias that occurs when people choose whether to participate, causing strong opinions to be over-represented.

Undercoverage

A type of bias that occurs when some members of the population are excluded or have a lower chance of selection.

Nonresponse Bias

A type of bias that occurs when selected individuals fail to respond, where responders may differ systematically from non-responders.

Convenience Sampling

A sampling method that selects individuals who are easiest to reach, leading to unrepresentative samples.

Response Bias

A type of bias that occurs when answers are inaccurate or influenced by data collection methods, such as leading questions or interviewer influence.

Control Group

A baseline group in an experiment used for comparison.

Placebo

A treatment that looks real but lacks the active ingredient.

Placebo Effect

A phenomenon that occurs when a subject's response is influenced by their expectations.

Comparison (Principle of Experimental Design)

The experimental design principle of comparing two or more treatments or groups.

Replication (Principle of Experimental Design)

The experimental design principle of using enough experimental units to distinguish treatment effects.

Control (Principle of Experimental Design)

The experimental design principle of keeping other conditions consistent across treatment groups.

Single-Blind Study

An experimental procedure where either the subjects or the researchers measuring responses do not know which treatment is received.

Double-Blind Study

An experimental procedure where neither the subjects nor the people interacting with them know which treatment is received.

Extraneous Variable

A variable other than the explanatory variable that could affect the response.

Confounding Variable

A variable whose effect cannot be separated from the effect of another variable, making it difficult to determine which variable caused an observed effect.

Completely Randomized Design

An experimental design in which all experimental units are allocated to treatments purely by random assignment, and results are compared.

Randomized Block Design

An experimental design where units are divided into blocks of similar characteristics (such as age), randomly assigned to treatments within each block, and compared within blocks.

Matched-Pairs Design

An experimental design that compares two treatments using paired, similar subjects or the same subject under both treatments.