9.1.4 Correlational Studies

• A correlational study examines the relationship between two or more variables
• Correlational studies differ from experimental studies because they do not manipulate variables
• Correlational studies can establish causation between variables.

  False
• Match the type of correlation with its description:

  Positive Correlation ↔️ Variables increase or decrease together

  Negative Correlation ↔️ As one variable increases, the other decreases

  Zero Correlation ↔️ No relationship between variables
• A positive correlation might be found between study time and exam
• Correlation always implies causation.

  False
• Causation means that one variable directly influences the other
• Why might ice cream sales and crime rates show a positive correlation?

  Shared underlying factor
• Arrange the variables in the following example to show their relationship: Ice cream sales, crime rates, and temperature.

  1️⃣ Temperature increases

  2️⃣ Ice cream sales increase

  3️⃣ Crime rates increase
• What is the key difference between correlation and causation in terms of statistical relationships?

  Causation implies direct influence
• Correlation indicates a relationship between variables, while causation means one variable directly influences the other
• Correlation always implies causation.

  False
• Why does a positive correlation between ice cream sales and crime rates not indicate causation?

  Shared underlying factor
• Causation requires direct evidence of influence
• Correlation can be mathematically represented as $A \uparrow \implies B \uparrow$ or $A \uparrow \implies B \downarrow$.
• Causation is mathematically represented as $A \implies B$, indicating a direct influence
• What is one advantage of using correlational studies?

  Explore relationships
• Correlational studies can identify relationships when experimental manipulation is not feasible.
• Correlational studies can predict outcomes based on observed relationships
• Why are correlational studies considered cost-effective?

  Less time and resources
• Correlational studies can analyze multiple variables simultaneously.
• Lack of causation is a key disadvantage of correlational studies
• What is the third variable problem in correlational studies?

  Unmeasured variable influence
• The directionality problem makes it difficult to determine which variable influences the other.
• What range do correlation coefficients fall within?

  -1 to +1
• A correlation coefficient of +1 indicates a perfect positive correlation
• A correlation coefficient of -1 indicates a perfect negative correlation
• What does an absolute value of $|r| > 0.7$ indicate for correlation strength?


  Strong correlation
• A correlation coefficient of $r =$$0.9$ between study time and exam scores represents a strong positive correlation.
• What does a correlational study examine?

  Relationship between variables
• In a positive correlation, both variables increase or decrease together
• A negative correlation means that as one variable increases, the other decreases.
• What does a zero correlation suggest about the relationship between two variables?

  No relationship
• Correlation does not imply causation
• Two variables can correlate without one causing the other.
• Correlation always implies causation between two variables.

  False
• Correlation is represented mathematically as $A \uparrow \implies B \uparrow$
• What third variable may influence both ice cream sales and crime rates?

  Temperature
• Correlational studies can predict future behaviors or outcomes
• Why are correlational studies considered cost-effective compared to experiments?

  Require less time and resources