Correlation | Simply Psychology
Descriptive studies do not test specific relationships between factors; causation : The act by which an effect is produced; in psychological research, the . aspect; an outcome measured to see the effectiveness of the treatment. independent After designing an experiment to test the hypothesis and collecting data from the . Explain why correlation does not imply causation. In contrast, correlational studies typically have low internal validity because nothing is Figure shows some hypothetical data on the relationship between the amount of stress people . This lesson explores the relationship between cause and effect and teaches you about the criteria for establishing a causal relationship, the.
Explain why a researcher might choose to conduct correlational research rather than experimental research or another type of non-experimental research. Interpret the strength and direction of different correlation coefficients. Explain why correlation does not imply causation. What Is Correlational Research?
Correlational research is a type of non-experimental research in which the researcher measures two variables and assesses the statistical relationship i.
There are many reasons that researchers interested in statistical relationships between variables would choose to conduct a correlational study rather than an experiment. The first is that they do not believe that the statistical relationship is a causal one or are not interested in causal relationships. Specifically, this strategy can be used to describe the strength and direction of the relationship between two variables and if there is a relationship between the variables then the researchers can use scores on one variable to predict scores on the other using a statistical technique called regression.
For example, while I might be interested in the relationship between the frequency people use cannabis and their memory abilities I cannot ethically manipulate the frequency that people use cannabis.
As such, I must rely on the correlational research strategy; I must simply measure the frequency that people use cannabis and measure their memory abilities using a standardized test of memory and then determine whether the frequency people use cannabis use is statistically related to memory test performance.
Similarly, correlation is used to establish the reliability and validity of measurements. For example, a researcher might evaluate the validity of a brief extraversion test by administering it to a large group of participants along with a longer extraversion test that has already been shown to be valid.
Neither test score is thought to cause the other, so there is no independent variable to manipulate. In fact, the terms Correlation is also used to establish the reliability and validity of measurements.
Another strength of correlational research is that it is often higher in external validity than experimental research. Recall there is typically a trade-off between internal validity and external validity. As greater controls are added to experiments, internal validity is increased but often at the expense of external validity.
In contrast, correlational studies typically have low internal validity because nothing is manipulated or control but they often have high external validity.
Since nothing is manipulated or controlled by the experimenter the results are more likely to reflect relationships that exist in the real world. Finally, extending upon this trade-off between internal and external validity, correlational research can help to provide converging evidence for a theory.
If a theory is supported by a true experiment that is high in internal validity as well as by a correlational study that is high in external validity then the researchers can have more confidence in the validity of their theory. These converging results provide strong evidence that there is a real relationship indeed a causal relationship between watching violent television and aggressive behavior.
Data Collection in Correlational Research Again, the defining feature of correlational research is that neither variable is manipulated. It does not matter how or where the variables are measured. Or a researcher could go to a shopping mall to ask people about their attitudes toward the environment and their shopping habits and then assess the relationship between these two variables.
Correlational Research – Research Methods in Psychology
Both of these studies would be correlational because no independent variable is manipulated. Correlations Between Quantitative Variables Correlations between quantitative variables are often presented using scatterplots. Taking all the points into account, one can see that people under more stress tend to have more physical symptoms. There is a negative relationship between stress and immune system functioning, for example, because higher stress is associated with lower immune system functioning.
The circled point represents a person whose stress score was 10 and who had three physical symptoms. A value of 0 means there is no relationship between the two variables.
Cause and Effect Relationship: Definition & Examples - Video & Lesson Transcript | jogglerwiki.info
With the exception of reliability coefficients, most correlations that we find in Psychology are small or moderate in size. It is not a good measure for nonlinear relationships, in which the points are better approximated by a curved line. Those who get too little sleep and those who get too much sleep tend to be more depressed.
Even though Figure 6. Nonlinear relationships are fairly common in psychology, but measuring their strength is beyond the scope of this book. It is a good idea, therefore, to design studies to avoid restriction of range.
Suppose that your results showed that not only did the students view the all-star athletes as more attractive and popular, but the self-confidence of the athletes also improved. Here we see that one cause having the status of an all-star athlete has two effects increased self-confidence and higher attractiveness ratings among other students.
Cause-Effect Criteria In order to establish a cause-effect relationship, three criteria must be met. The first criterion is that the cause has to occur before the effect.
Cause and Effect Relationship: Definition & Examples
This is also known as temporal precedence. In the example above, the students had to become all-star athletes before their attractiveness ratings and self-confidence improved. For example, let's say that you were conducting an experiment to see if making a loud noise would cause newborns to cry. In this example, the loud noise would have to occur before the newborns cried. In both examples, the causes occurred before the effects, so the first criterion was met.
Second, whenever the cause happens, the effect must also occur. Consequently, if the cause does not happen, then the effect must not take place. The strength of the cause also determines the strength of the effect. Think about the example with the all-star athlete. The research study found that popularity and self-confidence did not increase for the students who did not become all-star athletes.
Let's assume we also found that the better the student's rankings in sports; that is, the stronger they became in athletics compared to their peers, the more popular and confident the student became. For this example, criterion two is met.