Introduction to Statistical Thinking Flashcards

Vocabulary flashcards generated from lecture notes introducing statistical thinking, Big Data, key definitions, and types of statistics.

Data

Measurements and numbers historically generated to help solve a problem, which statisticians analyze using pictures and summary measurements to build predictive models.

Statistics

A formal way of thinking with data, defined as the science of learning from numbers with context by collecting, organizing, analyzing, and drawing conclusions.

Big Data

Data sets produced by our globally networked, internet-driven, sensor-laden world that are sufficiently large to be challenging to analyze at a typical data center.

Volume

An attribute of Big Data that refers to the scale of the data.

Variety

An attribute of Big Data that refers to the different forms data can take.

Velocity

An attribute of Big Data that refers to how fast data is being sent to the data processing and data management infrastructure.

Veracity

An attribute of Big Data that refers to the trustworthiness of the data.

Population

The total set of subjects or things we are interested in studying.

Frame

A list containing all members of the population.

Census

A survey that strictly includes all the elements or units in the frame.

Parameter

A fact or characteristic about the population.

Sample

A subset of the population which is used to gain insight about the population.

Statistic

A fact or characteristic about the sample.

Descriptive Statistics

The collection, organization, analysis, and presentation of data.

Inferential Statistics

Statistics with the objective to make reasonable guesses or inferences about population characteristics using sample data.

Measures of Central Tendency

Descriptive statistics measurements that include the mean, median, and mode.

Measures of Dispersion

Descriptive statistics measurements that include the range, variance, and standard deviation.