Single Correlation Between Self-Esteem And GPA

Single Correlation Between Self-Esteem And GPA

Self-esteem GPA

 

Third (unmeasured)

 

variable

 

Figure 2.5 Correlation does not imply cause and effect, because there are always three possibilities: (1) Variations in one variable (academic performance) may be causing variations in the second (self-esteem), (2) variations in the second may be causing variations in the first, or (3) a third variable may actually be causing both observed effects. Knowing only the single correlation between self-esteem and GPA doesn’t allow you to distinguish among these possibilities.

 

Methods in the Study of Personality 15

 

The use of random assignment rests on an assumption: that if you study enough people in the experiment, any important differences due to personality (and other sources as well) will balance out between the groups. Each group is likely to have as many tall people, fat people, depressed people, and confident people as the other group—if you study a fairly large number of participants and use random assignment. Anything that matters should balance out.

 

So, you’ve brought people to your research laboratory one at a time, randomly assigned them to the two conditions, manipulated the independent variable, and exerted experimental control over everything else. At some point, you would then measure the variable you think is the effect in the cause–effect relationship. This one is termed the dependent variable.

 

In this experiment, your hypothesis was that differences in success and failure on academic tasks cause people to differ in self-esteem. Thus, the dependent measure would be a measure of self-esteem (e.g., self-report items

 

(the pair of arrows labeled 3). Perhaps having a high level of intelligence causes a positive sense of self-esteem and also causes better academic performance. In this scenario, both self-esteem and academic performance are effects, and something else is the cause.

 

The possible involvement of another variable in a correlation is sometimes called the third-variable problem. It’s a problem that can’t be handled by correlational research. Correlations cannot tell which of the three possibilities in Figure 2.5 is actually right.

 

2.2.4: Experimental Research There is a method that can show cause and effect, how- ever. It’s called the experimental method. It has two defining characteristics. First, in an experiment, the researcher manipulates one variable—creates the existence of at least two levels of it. The one the researcher is manipulating is called the independent variable. This is the one the researcher is testing as the possible cause in a cause–effect relationship. When we say the researcher is “creating” two (or more) levels of this variable, we mean exactly that. The researcher actively creates a difference between the experience of some people and the experience of other people.

 

Sometimes psychologists do experiments in order to better understand what they’ve seen in correlational studies. Let’s illustrate the experimental method by doing just that. Let’s look closer at the example just discussed. Suppose you have a hunch that variations in academic performance have a causal effect on self-esteem. To study this possibility, you do an experiment, in which you hypothesize (predict) that academic outcomes cause effects on self-esteem.

 

You’re not going to be able to manipulate something like GPA in this experiment, but it’s fairly easy to manipulate other things with overtones of academic performance. For instance, you could arrange to have some people experience a success and others a failure on a task (using one rigged to be easy or impossible). By arranging this, you would create the difference between success and failure. You’d manipulate it—not measure it. You’re sure that a difference now exists between the two sets of people in your experiment, because you made it exist.

 

As in all research, you’d do your best to treat every participant in your experiment exactly the same in all ways besides that one. Treating everyone the same—making everything exactly the same except for what you manipulate— is called experimental control. Exerting a high degree of control is important to the logic of the experimental method, as you’ll see momentarily.

 

Control is important, but you can’t control everything. It’s rarely possible to have everyone do the experiment at the same time of day or the same day of the week. More

 

Random assignment is an important hallmark of the experimental method. The experimenter randomly assigns participants to a condition, much as a roulette wheel randomly catches the ball in a black or red slot.

 

obviously, perhaps, it’s impossible to be sure the people in the experiment are exactly alike. One of the main themes of this book, after all, is that people differ. Some people in the experiment are just naturally going to have higher self- esteem than other people when they walk in the door. How can these differences be handled?

 

This question takes us to the second defining characteristic of the experimental method: Any variable that can’t be controlled—such as personality—is treated by random assignment. In your experiment, you would randomly assign each participant to have either the success or the failure. Random assignment is often done by such means as tossing a coin or using a list of random numbers.

 

16 Chapter 2

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