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examBoard: AQA
examType: GCSE
lessonTitle: Understanding Association
Correlation is a statistical technique used in psychology to measure the relationship between two variables. When psychologists talk about correlation, they're looking at how changes in one variable might be linked to changes in another. For example, is there a relationship between the amount of time spent studying and exam scores?
Key Definitions:
There are three main types of correlation:
The correlation coefficient (r) tells us:
The closer a correlation coefficient is to +1 or -1, the stronger the relationship. Here's a rough guide to interpreting correlation strength:
0.1 to 0.3 (or -0.1 to -0.3)
Example: r = 0.2 between hours of sleep and reaction time
0.3 to 0.5 (or -0.3 to -0.5)
Example: r = 0.4 between exercise and mood improvement
0.5 to 1.0 (or -0.5 to -1.0)
Example: r = 0.7 between study time and exam scores
One of the most important things to remember about correlation is that it doesn't prove causation. Just because two variables are related doesn't mean one causes the other.
"Correlation does not imply causation" is one of the most important principles in psychological research. Just because two things happen together doesn't mean one caused the other!
There are several reasons why we can't assume causation from correlation:
Sometimes, an unseen third variable might be causing changes in both variables we're measuring.
Example: Ice cream sales and drowning deaths are positively correlated. Does ice cream cause drowning? No! The third variable is hot weather, which increases both ice cream consumption and swimming (leading to more drowning accidents).
Sometimes it's hard to tell which variable affects the other, or if they affect each other.
Example: Depression and social isolation are correlated. Does depression cause isolation, or does isolation cause depression? It could work both ways!
Psychologists follow specific steps when conducting correlational research:
Researchers measured daily screen time and sleep quality in 200 teenagers. They found a correlation coefficient of r = -0.65, indicating a strong negative correlation. As screen time increased, sleep quality decreased. However, they couldn't conclude that screen time caused poor sleep, as other factors might be involved (like stress levels or caffeine consumption).
Correlational research is used in many areas of psychology:
Studying relationships between teaching methods and learning outcomes
Examining how parenting styles relate to child behaviour
Investigating links between job satisfaction and productivity
When looking at correlational research, ask yourself these questions:
Sometimes, completely unrelated variables can show strong correlations by pure coincidence. For example, there's a strong positive correlation between cheese consumption and the number of people who die by becoming tangled in their bedsheets. This doesn't mean eating cheese causes bedsheet accidents - it's just a random coincidence! This reminds us to think critically about correlational findings.
Correlation is a powerful tool in psychological research that helps us understand relationships between variables. Remember these key points:
Understanding correlation helps psychologists identify important relationships and develop hypotheses for further research. While it can't tell us about cause and effect, it's an essential starting point for many psychological investigations.
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