Statistics Chapter 1 Notecards: Introduction and Sampling Methods

Vocabulary flashcards covering sampling concepts, data collection methods, and related topics from Chapter 1 notes.

Population

The entire group of individuals or elements under study from which a sample is drawn.

Sample

A subset of the population used to make inferences about the population.

Inferential Statistics

Methods used to draw conclusions about a population from a sample.

Need of a Sample

Reasons to study a sample: expense, time constraints, lack of accessibility, and sometimes destructive testing.

Advantages of Sampling

Lower cost, faster data collection, and improved data quality due to smaller, more homogeneous data.

Observational Study

Data collected by observing facts; no prior training; does not influence outcomes.

Experimental Study

Researcher controls the variables to determine how they influence responses.

Survey

The most common data collection method, typically involving questions to a sample.

Telephone Survey

Advantages: less costly; more truthful when not face-to-face. Disadvantages: not everyone has a telephone; some won’t answer; higher non-response.

Mailed Questionnaire

Advantages: less costly; can cover a wide geographic area. Disadvantages: high non-response.

Personal Interview

Advantages: in-depth responses. Disadvantages: high cost; some people may not be truthful in person.

Simple Random Sampling

The most common method; each element has an equal chance of selection; best when the population is homogeneous.

Picking Names Out of a Hat

A practical instantaneous sampling method; applicable when the population is small; uses a table of random digits; digits 0-9 are picked with replacement and recorded.

Random Digits Table

A table of random digits used to select samples; digits are drawn with replacement.

Stratified Random Sampling

Population divided into groups to ensure representation; samples are taken proportionally from each group.

Cluster Sampling

Population divided into many groups; a random sample of groups is chosen; a complete survey is performed within each selected group.

Systematic Sampling

If the complete frame is not available, the investigator samples periodically (e.g., every kth individual).

Multi-Stage Sampling

Like cluster sampling, but groups are subdivided into subgroups; samples of subgroups are obtained; the process may continue.

Convenience Sampling

Data collected from subjects that are convenient; may not be representative of the general population.

Technology in Statistical Analyses

Data can be very large; pencil-and-paper computations are impractical; computations are done with computers/calculators; statisticians must choose appropriate methods and interpret the results.

Sampling Frame

The complete list of population individuals from which a sample is drawn.

Homogeneous Population

A population in which elements are similar; simplifies simple random sampling.

Non-response

Failure of selected individuals to respond; can bias survey results and affect accuracy.