Correlational Research Statistical analyses of relationships between variables.
Dec 24, 2015
Purpose
• To identify relationships and assess how well one variable predicts* another.– *Meets psychology goal of prediction.
• It does NOT show cause and effect!
Importance
• Understanding correlations can help us lead safer and more productive lives.– Ex. Correlational studies have repeatedly found
high correlations between birth defects and a pregnant mother’s use of alcohol.
• This kind of information allows us to reliably predict our relative risks and to make informed decisions.
Caution
• A correlation between two variables does not mean that one variable causes another.– Ex. Some media reports about stress and cancer.
There is a correlation but does stress cause cancer? What else might contribute?
Types of correlation
• Positive• (same)
– Both factors move in the same direction
• Negative• (different)
– Both factors move in the opposite direction
Or
Or
Illusory Correlation
• If I wear my lucky socks then I will win my match.
The perception of a relationship between two variables when only a minor or absolutely no relationship actually exists...
Some potential questions that may be answered with correlational studies
• Are people who are experiencing severe stress more prone to develop physical illness than people who are not?
• Are children whose parent(s) have schizophrenia more likely to develop this disorder than other children?
• When someone needs help, is it more likely that someone would help them if many bystanders are present or just a few?
Quiz: What type of correlation?1. As a professional bowler’s score goes up, the amount of money
he makes goes up.Answer: Positive
2. As a professional golfer’s score goes down, the amount of money he makes goes up.Answer: Negative
3. A researcher finds that students who attend fewer classes get poorer grades.
Answer: Positive 4. The more ice cream sandwiches someone eats, the greater
their ability in math will beAnswer: Zero
5. Nick wore his lucky batting glove and hit two home runsAnswer: Illusory