Understanding Correlation and Causation

The video explores the misconception that eating pizza can reduce cancer risk, highlighting the difference between correlation and causation. It explains the third variable problem and illusory correlations using examples from video games and sports. The video also discusses the importance of correlational research and how it is used to study relationships between variables, emphasizing the use of statistical measures like Pearson's R.

What is the main takeaway from the study about pizza and cancer risk?

• Pizza is a part of a Mediterranean diet, which may reduce cancer risk.

• Pizza increases cancer risk.

• Eating pizza directly reduces cancer risk.

• Pizza consumption is unrelated to cancer risk.

What does the term 'correlation does not imply causation' mean?

• If two things are related, one must cause the other.

• Two related things are always unrelated.

• A relationship between two things does not mean one causes the other.

• Correlation always implies causation.

What is the 'third variable problem'?

• The third variable is unrelated to correlation.

• There is no such thing as a third variable.

• A third variable can be the actual cause of a perceived relationship between two variables.

• A third variable is always the cause of a correlation.

How might exposure to family violence relate to video game aggression?

• It directly causes video game aggression.

• It reduces the likelihood of playing video games.

• It is a third variable that might explain the link between video games and aggression.

• It has no relation to video game aggression.

What is an illusory correlation?

• A perceived relationship that does not actually exist.

• A real relationship between two variables.

• A correlation that is always positive.

• A correlation that is always negative.

Why do psychologists conduct correlational research?

• To prove causation between variables.

• To explore relationships and predict the presence or absence of variables.

• To establish definitive conclusions.

• To find unrelated variables.

What does a correlation coefficient of 0 indicate?

• A strong positive relationship.

• A strong negative relationship.

• A perfect correlation.

• No relationship between the variables.

What does a positive correlation imply?

• There is no relationship between the variables.

• As one variable increases, the other decreases.

• The variables are inversely related.

• As one variable increases, the other also increases.

How is the strength of a correlation visually represented?

• By the size of the data points.

• By the scatter of data points on a scatter plot.

• By the slope of the line of best fit.

• By the color of the scatter plot.

What does a negative correlation indicate?

• The variables are positively related.

• There is no relationship between the variables.

• As one variable increases, the other decreases.

• As one variable increases, the other increases.