Correlations Flashcards
What is a correlation?
A statistical technique that examines the relationship between two variables (called co-variables), showing how one changes in relation to the other.
What are co-variables?
Variables investigated within a correlation, which measure the association between them without establishing cause and effect.
What is a positive correlation?
When one co-variable increases, the other also increases. For example, the more people in a room, the higher the temperature.
What is a negative correlation?
When one co-variable increases while the other decreases. For example, the more exercise a person does, the lower their body weight.
What is zero correlation?
When there is no relationship between two co-variables. For instance, there is no link between rainfall in Peru and traffic in Manchester.
What is the difference between correlations and experiments?
Correlations examine relationships between variables without manipulation, whereas experiments manipulate an independent variable (IV) to measure its effect on a dependent variable (DV).
What are the strengths of using correlations?
Correlations are quick and economical, use secondary data, and can indicate trends for further research.
What are the limitations of using correlations?
Correlations only show relationships, not causation, and can be affected by third variables or biases.
What is a curvilinear relationship?
A relationship where the correlation changes direction, such as in the Yerkes-Dodson law, which states performance is optimal at a moderate arousal level but worsens if arousal is too high or too low.
How are positive and negative correlations identified on scattergrams?
Positive correlations show an upward trend, negative correlations show a downward trend, and zero correlations show no clear pattern.
What is a correlational hypothesis?
A hypothesis that predicts a relationship between co-variables, which can be directional (specific direction) or non-directional (no specific direction).
What is an intervening variable?
A third variable that might influence the relationship between the co-variables, making it difficult to establish causation.
