Sampling Methods and Introduction to Data Collection

Comprehensive vocabulary flashcards covering random sampling methods, forms of bias, observational studies versus experiments, and investigative questions.

Simple Random Sample (SRS)

A sampling method in which every possible group of individuals in the population has an equally likely chance of being selected.

Sampling Without Replacement

A sampling method where once an observational unit has been selected, that individual or item cannot be selected again.

Sampling With Replacement

A sampling process where selected individuals or items can be chosen more than once; when using technology to select an SRS, repeated numbers must be ignored.

Stratified Random Sample

A sampling method where the population is split into strata, and an SRS is selected from each stratum to create an overall sample.

Strata

Groups of individuals or items that share characteristics thought to be associated with one of the variables being measured in a study.

Cluster Random Sample

A sampling method where the population is divided into clusters, an SRS of clusters is chosen, and a census is performed on each selected cluster.

Clusters

Groups in the population that are located near each other.

Systematic Random Sample

A sampling method where every $n\text{th}$ person or item is surveyed from a list of all possible participants/items in the sampling frame, provided the order is not associated with the variable studied.

Sampling Frame

A list of all possible participants or items from which a sample is selected.

Sampling Variability

The sample-to-sample differences that occur because each random draw selects different individuals, leading to different values for the measured variables.

Convenience Sample

A non-random sampling method that selects individuals who are easiest to reach, introducing bias and preventing generalization to the larger population.

Voluntary Response Sample

A sample consisting of individuals who choose themselves to participate (e.g., calling into a radio station), which typically overrepresents individuals with strong opinions.

Nonresponse Bias

A bias that occurs when a large proportion of selected individuals fail or refuse to respond, resulting in an incomplete sample where responders may differ systematically from non-responders.

Response Bias

A systematic pattern of incorrect responses caused by the wording of a question, the setting, or the behavior/characteristics of the interviewer.

Undercoverage

A type of bias that occurs when certain groups or members of the population are omitted or have a lower chance of being chosen in the sample.

Inference

The procedure of using sample statistics to answer questions and draw conclusions about population parameters.

Experiment

A hands-on method of data collection in which a researcher actively manipulates variables and imposes treatments to measure their effects on response variables.

Observational Study

A hands-off method of data collection where researchers merely gather data without manipulating variables or assigning treatments.

Response Variable

The variable that measures the outcome of a statistical study.

Explanatory Variable

A variable that predicts or explains changes in the response variable.

Factors

The explanatory variables that are manipulated in an experiment.

Levels

The specific values or settings of a factor in an experiment.

Treatments

The specific experimental conditions applied to experimental units, formed by the combinations of factor levels.

Experimental Units

The individuals, items, or non-human entities to which treatments are applied in an experiment.

Subjects

Human experimental units participating in an experiment.

Retrospective Study

An observational study that gathers data from the past.

Prospective Study

An observational study that gathers data in real time going forward.

Survey

A data collection method in which information is collected by asking questions of a sample.

Census

A data collection method in which information is collected by asking questions of an entire population.

Extraneous Variable

A variable other than the explanatory variable that could still impact the response variable.

Confounding Variable

A variable that is associated with both the explanatory variable and the response variable, clouding the true relationship between them.

Causal Conclusion

A conclusion establishing cause-and-effect between variables, which is only justifiable when treatments are randomly assigned to experimental units in an experiment.

Generalizability

The extent to which study findings apply to a broader population, which is valid only when subjects or observational units are randomly sampled from that target population.