Module 1.1 Variables & Selecting Analyses

Vocabulary flashcards covering scales of measurement, population vs. sample concepts, statistical inference, variable roles, and rules for selecting statistical analyses based on variable types.

Nominal Scale

A scale of measurement in which a variable's levels are different only in name, with no numerical or ordinal relationship (e.g., Eye Color, Birth State, Favorite Color).

Ordinal Scale

A scale of measurement in which variable levels have a natural ordering, but the intervals between levels are not necessarily equal (e.g., Military Rank, Soft Drink Size, Agreement ratings).

Interval Scale

A scale of measurement where a unit interval always represents the same quantity, but zero is arbitrary and does not mean total absence (e.g., Temperature in $^\text{o}\text{F}$ or $^\text{o}\text{C}$, Calendar Year, Time of Day, Elevation).

Ratio Scale

A scale of measurement with consistent unit intervals and a true zero point representing complete absence, allowing meaningful ratios (e.g., Age, Amount of money in pocket, Number of Children in Family).

Population

The complete set of all possible scores or subjects of interest in a study.

Sample

The measured subset of a population used to represent the larger group.

Inference

The process of drawing conclusions about a population based on observations and measurements obtained from a sample.

Independent Variable

The variable that is manipulated or used to categorize groups (often representing the cause or treatment) in an analysis.

Dependent Variable

The variable that is measured as the outcome or effect (e.g., symptom severity) to assess the impact of the independent variable.

Selecting Statistical Analysis

The framework for choosing an appropriate analytical method based on whether the Independent Variable and Dependent Variable are categorical or continuous.

Chi-Square ($\times^2$) Test of Independence

A statistical analysis selected when both the Independent Variable and Dependent Variable are categorical.

Logistic Regression

A statistical analysis used when the Independent Variable is continuous and the Dependent Variable is categorical.

Discriminant Function Analysis

An analytical method used to predict a categorical Dependent Variable using one or more continuous Independent Variables.

$t$-test

A statistical test used to compare means when the Independent Variable is categorical and the Dependent Variable is continuous.

Analysis of Variance (ANOVA)

A statistical analysis used to test differences among group means when the Independent Variable is categorical and the Dependent Variable is continuous.

Correlation

A statistical procedure used to evaluate the association between two continuous variables.

Regression

A statistical method used to examine and model the relationship between a continuous Independent Variable and a continuous Dependent Variable.