Correlational research is a form of non-experimental study method, in which a researcher measures two variables, understands and assesses the statistical relationship between them with little or no effort to control any extraneous variables. In other words, a correlation refers to a relationship between two variables. Correlation can be strong or weak, as well as positive or negative. In other cases, there might be no or zero correlation at all between the variables of concern. The aim of correlational research is to discover variables that have some kind of connection to make the point that a change in one creates some change in the other. In this article we will discuss correlational research in detail.
How Correlational Researches Work:
Correlational researches are a type of research frequently used in psychology as a beginning way to collect information with reference to a subject or in situations where conducting an experimentation is not possible. The correlational research involves looking at relationships among two or more variables. Whereas researchers can make use of correlations to see if a connection exists, the variables themselves are not in the control of the researchers.
One more point is that while correlational research can disclose if a connection exists between variables, this type of method cannot establish that changes to one variable direct changes to an additional variable. In other words, correlational methods cannot demonstrate cause and effect relationships. Correlational study has a number of strengths and weaknesses, so it’s significant to decide which research method is finest for particular circumstances.
Correlation is also used to set up the reliability and validity of measurements. For example, an examiner might assess the validity of a concise extraversion test by administering it to a huge group of participants all along with a longer extraversion test that has previously been exposed to be valid. Then the experimenter might ensure to observe whether participants’ scores on the concise test are strongly correlated with their results on the longer one. So there is no independent variable to control. In fact, the terms independent variable and dependent variable do not relate to this type of research.
Types of Correlational Research:
Basically, there are three types of correlational research which are: positive correlational research, negative correlational research, and no correlational research. All of these types are defined by certain characteristics.
- Positive Correlational Research:
Positive correlational research is a type of research connecting two variables that are statistically parallel where an increase or decrease in one variable establishes a like change in the other. For an example: when an increase in employee’s salary results in an increase in the prices of goods and services and the other way round.
- Negative Correlational Research:
Negative correlational research is a type of research method linking two variables that are statistically opposite where an increase in one of the variables results in an alternating effect or decrease in the other variable. For example: a negative correlation is if the increase in goods and services causes a decrease in requirement and vice versa.
- Zero Correlational Research:
Zero correlational research is a type of research that includes two variables that are not essentially statistically linked. In this case, a transformation in one of the variables might not activate a parallel or alternate change in another variable.
Zero correlational research handles for variables with unclear statistical relationships. For example: material goods and patience can be variables in zero correlational research as they are statistically independent.
A correlation coefficient is a significant value in correlational research which indicates either the interrelationship between two variables is positive, negative or zero. It is generally represented with the sign (r) and is an element of a series of probable correlation coefficients from -1.0 to +1.0.
The strength of a correlation among quantitative variables is naturally calculated with a statistic called Pearson’s Correlation Coefficient or (Pearson’s r). A positive correlation is indicated by a value of 1.0, an ideal negative correlation is indicated by a value of -1.0 whereas zero correlation is indicated by a value of 0.0.
It is significant to notice that a correlation coefficient only reflects the linear relationship between two variables. It does not confine non-linear relations and cannot split dependent and independent variables. The correlation coefficient helps you to decide the level of statistical connection that exists among variables.
Data Collection in Correlational Research:
The important quality of correlational research is that none of the variables are manipulated. It does not matter how or where the variables are calculated. A researcher could have respondents come up to a laboratory to include an automatic backward digit length assignment and a computerized uncertain decision-making assignment and then evaluate the relationship among participants’ scores on the two assignments. Otherwise a researcher might go to a shopping mall to inquire about their attitudes toward the environment and their shopping practice and then evaluate the relationship among these two variables. Two of these studies would be correlational while no independent variable is manipulated.
Data Collection Methods in Correlational Research:
Methods of data collection in correlational research are the research methodologies adopted by persons moving out correlational research in selection to conclude the linear statistical relationship among two variables. These methods are used to collect information in correlational research.
The three methods of data collection in correlational research are: naturalistic observation, archival data, and the survey method. All of these methods are described as below:
Naturalistic observation is a data collection method of correlational research that involves observing people’s behaviors as exposed in the natural environment where they live, over a period of time. It is a type of research-field method that involves the examiner paying close attention to natural activities patterns of the subjects under consideration.
This method involves observing and recording the variables of concentration in the natural setting exclusive of intrusion or treatment by the experimenter. This method is really demanding as the examiner has got to take more concern to make sure that the subjects do not believe that they are being observed as well they move away from their usual conduct patterns. It is best for all subjects under examination to remain unknown in order to keep away from a violation of privacy.
Advantages and Disadvantages of Naturalistic Observation:
The advantages of naturalistic observation contain:
- It gives the researcher the chance to observe the variable of interest in a natural setting
- It can propose ideas for additional research
- It might be the single opportunity if lab testing is not achievable
The disadvantages of naturalistic observation consist of:
- It can be time-consuming and costly
- It does not tolerate for systematic control of variables
- Researchers cannot control extraneous variables
- Subjects might be alert of the observer and might act in a different way as an effect
Archival data is a type of data collection method that involves manufacture use of previously gathered information or data about the variables in correlational research. Because this method involves using statistics that is already gathered and analyzed, it is typically directly to the point. For example, experimenters analyzed the actions of soldiers who served in the Civil War to study further about post traumatic stress disorder (PTSD) in an experiment known as ‘The Irritable Heart’.
This method helps an examiner to follow already firm statistical patterns of the variables or subjects. This method is not as much expensive, saves time and provides the investigator with more not reusable data to work with. Though, it has the difficulty of data precision as significant information might be misplaced from earlier research as the investigator has no control over the data compilation procedure.
Advantages and Disadvantages of Archival Research:
The advantages of archival research contain:
- The experimenter cannot initiate changes in contributor’s performance
- Frequently less costly than other study methods
- Huge number of data offer an improved vision of trends, relations, and outcomes
Disadvantages of archival research include:
- The experimenter has no charge over how information was collected
- Prior research might be unreliable
- Main dates might be absent from the proceedings
The survey method is the most general means of correlational research; particularly in fields like psychology. It involves random sampling of the variables or the subjects in the research in which the respondents fill a questionnaire consisting of the subjects of concentration. Surveys and questionnaires are amongst the most familiar methods used in any psychological research. In this method, a random sample of participants finishes a survey, test, or questionnaire that relates to the variables of choice. Random sampling is a very important part of ensuring the generalizability of the study results.
This method is very stretchy as experimenters can collect large amounts of data in a very short period of time. On the other hand, it is subject to survey reaction bias and can also be exaggerated by biased survey questions or under depiction of survey participants.
Advantages and Disadvantages of the Survey Method
The advantages of the survey method consist of:
- Fast, easy and cheap
- Researchers can gather huge amounts of data in a comparatively short period of time
- Extra flexible than a few other methods
The disadvantages of the survey method contain:
- Respondents can influence the result
- Some participants strive to gratify the examiner, stretch out to make themselves look improved
- Can be exaggerated by an illusory sample or deprived survey questions
Limitations of Correlational Studies
While correlational research can propose that there is a relationship between two variables, it cannot establish that one variable causes a change in another variable. In other words, correlation does not entail causation. A statistical relationship between two variables, X and Y, does not essentially signify that X causes Y. It is also probable that Y causes X, or that a third variable, Z, causes both X and Y
For example, a correlational study might propose that there is a connection between academic success and self-esteem, but it cannot show if academic success actually causes changes in self-esteem. Other variables might take part in a role, including social relationships, thinking abilities, personality traits, socioeconomic status, and countless other factors.
FAQs about Correlational Research
What is correlational research used for?
Correlational studies are a type of research often used in psychology as a preliminary way to gather information about a topic or in situations where performing an experiment is not possible. The correlational method involves looking at relationships between two or more variables.
What is a correlational study design?
A correlational study is a type of research design where a researcher seeks to understand what kind of relationships naturally occurring variables have with one another. In simple terms, correlational research seeks to figure out if two or more variables are related and, if so, in what way.
What is experimental and correlational research?
Correlational versus Experimental Studies. Psychological studies vary in design. In correlational studies a researcher looks for associations among naturally occurring variables, whereas in experimental studies the researcher introduces a change and then monitors its effects.
What does correlational study mean?
A correlational study determines whether or not two variables are correlated. This means to study whether an increase or decrease in one variable corresponds to an increase or decrease in the other variable.