Pre-Reading 2 Part 1: The Correlational Method
The word correlation has been used for some time in common language to mean that a relationship exists between two things. When we talk about correlations in social psychology we are actually referring to a mathematical relationship called the “Pearson Correlation Coefficient R”. If you take a statistics course you will learn about the actual mathematical formula for calculating the “Pearson R”, but since this isn’t a stats course you just need to keep a couple things in mind.
The Correlation Coefficient can have a value from -1 to +1. There are two pieces of information that the value can tell you. First, the sign (either negative or positive) tells you the direction of the relationship. A positive (+) correlation indicates that as one variable of interest increases the other increases. For example, GNP (Gross National Product) and mortality are positively correlated. In other words, countries that are wealthier tend to have people that live longer. A negative (-) correlation indicates that as one variable increases the other decreases. For example, GNP (Gross National Product) is negatively correlated with birth rate. Wealthier countries, with higher GNPs, tend to have populations that have fewer children per household. The other thing to keep in mind about the Pearson R is the size of the relationship. We need to ignore the sign, and just look at the absolute value (usually written like this ½R½). In cases where the absolute value is close to zero, then the relationship between the two variables is very weak. If the absolute value is close to one, then the relationship is very strong.
Often, the point of doing correlational research is to find out if two or more variables are related to each other. If they are related, then the question moves to the nature of the relationship. “Is there a relationship between watching violent television and aggressive behavior?” If it turns out that there is no relationship between these things (finding a correlation that is equal to zero), then that’s the end of it. If it turns out that there is a correlation between these things then the strength and direction of this relationship can be important. Even when a strong correlation between variables is found we must be careful when we interpret the relationship. The phrase, “Correlation does not equal causation” is important. Just because we know that two concepts are related, we cannot (based on correlational research design) make any claims about which variable causes the other.
You are now ready to read pages 29 through 41 in your textbook. After you have read the Assignment, go to the Quiz 2 Part 1 on the ANGEL account and take the quiz. When you are done with the reading and the quiz go to “Pre-Reading Commentary 2 Part 2”.