Correlations for Smart People Lecture Review

Flashcards for key concepts from the correlations lecture.

Correlation

A statistical measure that describes the degree and direction of the relationship between two variables.

Scatterplot

A graph that shows the relationship between two variables by displaying data points on a two-dimensional plane.

Pearson correlation coefficient

A measure of the linear relationship between two variables, ranging from -1 to 1.

Outliers

Data points that differ significantly from other observations and can affect statistical results.

Dependent variable

The variable that is being tested and measured in an experiment.

Independent variable

The variable that is varied or manipulated to observe its effects on the dependent variable.

Positive correlation

A relationship where both variables increase or decrease together.

Negative correlation

A relationship where one variable increases as the other decreases.

Magnitude

The strength of the correlation, regardless of direction.

Coefficient of determination (R²)

A measure indicating the proportion of variance in the dependent variable explained by the independent variable(s).

Nonparametric correlation coefficients

Statistical methods suitable for data that do not follow a normal distribution or when sample sizes are small.

Kendall's tau

A nonparametric measure of correlation that assesses the strength and direction of the association between two variables.

Spearman's rank-order correlation

A widely used nonparametric measure that assesses the strength and direction of the association between two ranked variables.

Curvilinear correlation

A relationship between two variables that is best described by a curved line.

Third-variable problem

The possibility that an unmeasured third variable is causing the observed correlation between two variables.

Linearity

The property of a relationship between two variables that can be described with a straight line.

Z-score

A measure that describes a value's position relative to the mean of the data, expressed in standard deviations.

Residuals

The differences between observed values and the values predicted by a model.

Effect size

The strength of a relationship between two or more variables.

Probability

The likelihood that a correlation is due to chance, often assessed using p-values.