Chapter 1: Introduction to Statistics and Levels of Measurement

Vocabulary practice flashcards covering fundamental statistical concepts, study designs, variable classifications, and levels of measurement from Chapter 1.

Statistics

The practice of looking at data and applying tests to find out either that what you observe is what you expected or that your observation differs enough from what you expected that you need to change your expectations.

Empirical method

A way of gathering information through systematic observation and experimentation.

Variable

The changing characteristic being measured in a study.

Probability

The likelihood that an outcome will occur.

Population

The whole group of interest in a study (sometimes referred to as the reference population).

Sample

A subset or group selected from the population to be included in a study.

Parameter

A descriptive result or measured characteristic calculated from the whole population.

Statistic

An estimate or value derived from sample data, used to estimate a population parameter.

Estimate

A preliminary approximation.

Quantitative measure

A measure that reflects a numeric amount.

Qualitative measure

A measure that describes or characterizes an attribute without conveying quantitative information, rank, or distance.

Independent variable

A variable measured or controlled by the experimenter (variable $x$); the suspected causative agent thought to affect the outcome.

Dependent variable

The outcome variable or final result (variable $y$); the measured effect that depends on the independent variable.

Continuous variable

A quantitative variable that has an infinite number of potential values, with the value being measured falling somewhere on a continuum containing in-between values.

Categorical variable

A variable (also known as a discrete variable) that has a finite number of classification groups or categories, which are usually qualitative and lack fractional or in-between values.

Nominal data

Data that indicate a difference only, organized into categories that are exhaustive and exclusive but not rank-ordered.

Ordinal data

Data whose categories are exhaustive, exclusive, and rank-ordered, but lack equal or known intervals between categories.

Interval data

Data whose categories are exhaustive, exclusive, and rank-ordered, with equally spaced intervals, but without a true zero point of origin.

Ratio data

Data whose categories are exhaustive, exclusive, and rank-ordered, with equally spaced intervals and a true "$0$" value point of origin where the variable is absent.

True zero point of origin

A characteristic of ratio-level data where the value indicates total absence of the variable, allowing the calculation of meaningful ratios and proportions.

Measurement scales

Standardized numeric ranges (such as a $0$ to $10$ or $1$ to $10$ scale) used to artificially create equal intervals for ordinal variables so they can be analyzed at higher levels of measurement.