Chapter 2: Looking at Data – Relationships

These flashcards cover key terms and concepts related to relationships in statistics, focusing on associations, correlation, and regression analysis.

Association

In statistics, the term for relationships between variables, where knowing about one variable provides information about another.

Independent Variable (IV)

The variable that is manipulated or controlled in a study to observe its effect on the dependent variable.

Dependent Variable (DV)

The variable being measured or tested in an experiment, which is affected by changes in the independent variable.

Positive Linear Association

A relationship where high values of one variable are associated with high values of another variable.

Negative Linear Association

A relationship where high values of one variable are associated with low values of another variable.

Correlation Coefficient (r)

A numerical measure ranging from -1 to 1 that indicates the strength and direction of the linear relationship between two quantitative variables.

Outlier

A data point that lies far outside the overall pattern of other observations, which can influence statistical results.

Least Squares Regression Analysis

A method to find the best-fit line for predicting values of a response variable from an explanatory variable by minimizing the sum of the squares of the residuals.

Residual

The difference between the observed value of a variable and the value predicted by a regression line.

Lurking Variable

A variable not included in a study that may influence the relationship between the explanatory and response variables.

Causation

The relationship where one variable directly affects another variable, as opposed to mere correlation.

Extrapolation

The process of estimating beyond the range of data used to create a model or regression line, which may lead to inaccurate predictions.

Scatterplot

A graphical representation of the relationship between two quantitative variables, using points to represent individual data observations.

Confounding Variables

Variables that obscure the effects of another variable on a response variable, making it difficult to determine causation.

Strength of Association

Refers to how closely the data points cluster around a line in scatterplots, indicating the reliability of the correlation.