Tulane University PSYC 3130 - Chapter 8 Learning Objectives

This set of flashcards focuses on key concepts from the lecture on bivariate correlation and association claims, including definitions, important statistics, and research methodology.

Bivariate Correlation

A statistical measure that describes the strength and direction of a relationship between two quantitative variables.

Association Claim

A statement that suggests a relationship between two variables, which is supported by correlational studies.

Scatterplot

A graphical representation of the relationship between two quantitative variables, used to estimate results from a correlational study.

Correlation Coefficient

A numerical value that represents the strength and direction of a linear relationship between two quantitative variables.

Categorical Variable

A variable that can be divided into categories, often analyzed in correlational studies using bar graphs.

Construct Validity

The extent to which a variable accurately measures the concept it is intended to measure.

Statistical Validity

The degree to which the results of a study are accurate and reliable, avoiding distortions from data features like outliers.

Outliers

Data points that differ significantly from other observations in the dataset, which can distort correlation coefficients.

Effect Size

A measure of the strength of a relationship between two variables, crucial for understanding correlation in a study.

Confidence Intervals

A range of values that is likely to contain the true value of a population parameter.

Replication

The process of repeating a study to confirm the consistency of its findings and enhance its validity.

Curvilinear Relationship

A relationship between two variables that is not a straight line, which can be identified by inspecting a scatterplot.

External Validity

The extent to which the findings of a study generalize to settings, people, or time periods beyond the study.

Moderator

A variable that affects the strength or direction of the relationship between two other variables.

Covariance

A measure of how much two random variables vary together, playing a critical role in association claims.

Causal Claim

A statement that implies a cause-and-effect relationship between variables, differentiated from mere association.

Causal Features

Characteristics that help distinguish a causal claim from an association claim, such as temporal precedence and manipulation.