Random Sampling and Data Collection - AP Statistics

A sample where each member has an equal chance of selection. Ensures randomness and prevents selection bias.

Population divided into strata; random samples taken from each stratum. Ensures representation from each subgroup.

Select every $k^{th}$ member from a list of the population. Provides systematic coverage with random starting point.

To divide the population into clusters and randomly select entire clusters. Efficient when population naturally groups together.

Sample selected based on ease of access. Not random; prone to selection bias.

Systematic error that results in a non-representative sample. Creates unrepresentative samples and invalid conclusions.

Bias introduced when responses are not obtained from all selected participants. Creates incomplete data and potential bias.

Bias that occurs when participants provide inaccurate responses. Results from measurement errors or participant dishonesty.

Parameter describes a population; statistic describes a sample. Parameters are fixed values; statistics are calculated estimates.

Conducted to test the feasibility and improve the design of the study. Identifies problems before full-scale data collection.

Reduces bias and ensures each member of the population has an equal chance of selection. Creates representative samples for valid inference.

To serve as a baseline for comparison with the treatment group. Enables comparison to measure treatment effects.

Randomly assigning subjects to treatment groups to control for confounding variables. Minimizes confounding and ensures fair comparison.

Neither the subjects nor the researchers know who receives the treatment. Eliminates bias from expectations and placebo effects.

Repeating an experiment to confirm results. Increases confidence in experimental results.

Concealing information from participants to reduce bias. Prevents bias from participant and researcher expectations.

An inactive substance given to the control group in an experiment. Controls for psychological effects of treatment.

An observation that lies an abnormal distance from other values. May indicate data errors or unusual observations.

The probability distribution of a given statistic based on a random sample. Foundation for statistical inference about populations.

The entire group of individuals or instances about whom we hope to learn. Target group for statistical inference and conclusions.

Larger samples reduce sampling error and increase result reliability. Follows law of large numbers for accuracy.

Sampling method that involves multiple stages of sampling, often combining methods. Complex but efficient for large, dispersed populations.

It controls for confounding variables and reduces bias. Essential principle for valid experimental design.

Repeating an experiment to confirm results. Increases confidence in experimental results.

A sample where each member has an equal chance of selection. Ensures randomness and prevents selection bias.

Sampling method where quotas are set for different subgroups of the population. Non-random method that can introduce bias.

Subjects change behavior because they know they are being observed. Threatens validity of observational studies.

A list of all individuals or units in the population from which the sample is drawn. Should ideally include all population members.

Occurs when some members of the population are inadequately represented in the sample. Results from incomplete sampling frame coverage.