Psychology: Correlations vs. Experiments

Questions and Answers

What is the key difference between correlations and experiments?

Correlations do not reliably point to a cause-and-effect relationship, whereas experiments do.

What does a correlational study not tell us?

Why the co-variables are related.

Why should correlations be treated cautiously?

Outliers considerably distort the coefficient, and small samples are not generalizable.

When should greatest caution be taken with correlations?

When the sample size is less than 100. Signup and view all the answers

What are the choices for interpretation of correlations?

All of the above. Signup and view all the answers

What is a cause and effect explanation?

The researcher could decide that one variable actually caused the other to change. However, a correlation does not prove this. Signup and view all the answers

What is a third variable explanation?

Something in the background other than the measured variables is creating the relationship. Signup and view all the answers

What is a chance relationship?

Sometimes the result is just a statistical anomaly, which occasionally happens with large samples. Signup and view all the answers

Study Notes

Key Differences Between Correlations and Experiments

Correlations do not establish cause-and-effect; experiments can determine causal relationships.

Limitations of Correlational Studies

Correlational studies fail to explain the reason behind the relationship between co-variables.

Cautions Regarding Correlations

Outliers can skew correlation coefficients, making results less reliable.
Smaller sample sizes may not accurately reflect broader populations.

When to Exercise Caution with Correlations

Extreme caution is advised when the sample size is fewer than 100 participants.

Interpretation Options for Correlations

Possible interpretations include:
- A direct cause-and-effect relationship.
- The influence of a third variable affecting both co-variables.
- A mere chance occurrence due to randomness.

Cause and Effect Explanation

Researchers may assume a direct causal link between two variables, yet correlation alone does not validate this assumption.

Third Variable Explanation

A third variable may influence the relationship between two measured variables, such as hard work leading to both better grades and higher income.

Chance Relationship

Some correlations may arise purely by chance, particularly in larger sample sizes, leading to statistical anomalies.

Description

Explore the key differences between correlational studies and experiments in psychology. This quiz will guide you through the limitations, cautions, and interpretation options of correlations, helping you understand the importance of establishing causal relationships in research.