Selecting the Sample (feb 4th)

These flashcards cover key vocabulary and concepts related to the sampling process in research, essential for understanding how to select and analyze a sample.

Sample

The process of choosing members of a population to be included in a study.

Population

All possible individuals making up a group of interest in a study.

Target Population

The general population that the study seeks to understand.

Source Population

The specific individuals from which a representative sample will be drawn.

Sample Population

Individuals asked to participate in the study.

Study Population

Eligible participants from the sample.

Probability Sampling

Sampling method where the likelihood of any one member of the population being selected is known.

Non-Probability Sampling

Sampling method where the likelihood of selecting any one member of the population is not known.

Sampling Error

The difference between the characteristics of the sample and those of the population from which it was selected.

External Validity

The degree to which findings can be generalized to a larger population.

Response Rate

The percentage of people in the sample who complete the survey.

Selection Bias

Occurs when the members of the study population are not representative of the source population.

Nonresponse Bias

Bias introduced when non-respondents differ from respondents in significant ways.

Generalization

The ability to apply findings from a sample to a larger population.

Simple Random Sampling

Each member of the population has an equal and independent chance of being selected.

Stratified Random Sampling

Ensures representation from important subgroups that may have different characteristics.

Cluster Sampling

Divides the population into sections, selects some of those sections, and includes all members from the selected sections.

Convenience Sampling

Sampling method that involves taking participants from wherever they are easily accessible.

Quota Sampling

Selecting a predetermined number of individuals with desired characteristics without regards to randomness.

Measurement Error

Anything that could go wrong with your decisions in a study that may affect the results.

Type I Error

The probability of a study yielding a statistically significant result when there is no actual difference.

Type II Error

The probability of a study not finding a statistically significant result when there is actually a difference.