Chapter 12: Correlational Research Designs

Flashcards reviewing key vocabulary and concepts from a lecture on correlational research strategies.

basics of correlational design and how does it differ in validity?

Correlational designs explore relationships between variables without manipulating them. Low internal validity, high external validity.

correlations coefficients Direction

Shows the strength and direction of the relationship between two variables. Positive (both increase/decrease together) or Negative (one increases, the other decreases)

correlation coefficient Form

Most are linear, but some can be curvilinear

correlation coefficient Strength

The correlation measures the consistency of the relationship and varies from 0 (no
relationship at all) to 1 (perfect relationship).

Pearson Correlation

Measures the strength and direction of a linear relationship between two continuous variables.

Spearman Correlation

Measures the strength and direction of a linear relationship between two ranked (ordinal) variables.

Point-Biserial Correlation

Correlation between discrete (nominal) and continuous (interval/ratio) variables.

Phi-Coefficient

Measures the strength of the relationship between two categorical (nominal) variables.

Prediction (in Correlation)

Using one variable to accurately predict another when a systematic relationship exists.

Validity (using Correlation)

Demonstrating a test's validity by correlating its scores with other intelligence measures.

Reliability (using Correlations)

Determining the reliability of a measurement procedure by assessing the stability and consistency of measurements.

Theory Verification (using Correlation)

Testing psychological theories by determining the correlation between two variables, complementing experimentation.

Regression

A statistical procedure that determines the equation for the straight line that best fits a specific set of data.

Causation

Correlation does not equal causation; a third variable may be responsible for the relationship.

Restricted Range

The range of scores can affect the strength of the correlation; Blank ranges can weaken it.

Outliers

Blank can disproportionately influence the correlation coefficient.

Misinterpreting the value of r

The correlation coefficient (r) is not a percentage. To understand how much one variable predicts another, square the r value to get the coefficient of determination (r²).

Correlational Research Strategy

Aims to demonstrate relationships between variables without establishing cause-and-effect.

Positive Correlation

A relationship where two variables increase or decrease together, indicated by a Blank correlation coefficient.

Negative Correlation

A relationship where two variables move in opposite directions, indicated by a blank correlation coefficient.

Coefficient of Determination (r²)

Measures the proportion of variability in one variable that can be determined from the relationship with the other variable.

Correlational Research

Deals with one group of participants and measures two variables from the same group.

Linear Relationship

A straight-line relationship between two variables, commonly measured by correlation coefficients.

Curvilinear Relationship

A relationship between two variables that is not a straight line, requiring special correlations to measure.