Flashcards Statistics: Key Concepts in Data Types, Sampling, and Measures

Qualitative

Data that describes categories, qualities, or types rather than numbers.

Quantitative

Data that represents numerical amounts that can be counted or measured.

Discrete

Numerical data made of separate countable values, usually whole numbers.

Continuous

Numerical data that can take any value within a range, including decimals.

Statistic

A numerical value that describes a sample.

Parameter

A numerical value that describes an entire population.

Population

The entire group of individuals or items you want information about.

Sample

A smaller group selected from a population to be studied.

Experiment

A study where researchers assign a treatment or condition to subjects.

Observational Study

A study where researchers observe and record without assigning treatments.

Simple Random Sample

A sample where every individual has an equal chance of being selected.

Systematic Random Sample

A sample chosen by selecting every nth individual from a list after a random starting point.

Stratified Random Sample

A sample made by dividing the population into groups and randomly sampling from every group.

Cluster Random Sample

A sample made by randomly selecting entire groups and studying everyone in the selected groups.

Mean

The average of a set of numerical values.

Median

The middle value when the data are arranged in order.

Mode

The value or category that occurs most often.

Central Tendency

A measure that describes the center or typical value of a data set.

Standard Deviation

A measure of how spread out the data are around the mean.

Outlier

A value that is unusually high or low compared with the rest of the data.

Resistant

A statistic that is not greatly affected by extreme values or outliers.