From a broader perspective, the quantitative research method is classified into two groups. The first one is experimental, while the other one is non-experimental. A correlation study is one of the non-experimental types of quantitative research methods. In this study, you have to define some variables, including dependent as well as independent. After defining variables, you have to identify the relationships existing between the variables. The most commonly observed relations are statistical ones. You cannot get these results from an experimental study. Sometimes, you may require these results for designing an experiment. So, let’s discuss why there is a need to build a connection between experimental studies with correlational research.
What are the Three Types of Correlational Research?
There are three correlational studies which play a significant role in finding effective results. These three types are mentioned below:
1. Cohort Studies
The cohort studies set the benchmark to explain the characteristics of multiple variables.
2. Cross-Sectional Studies
Cross-sectional studies are one type which is used to make a comparison of variables, but the main point is the number of comparisons. In cross-sectional studies, you are allowed to make a single comparison.
3. Case-Control Studies
Case-control studies are made when you have to style comparisons between known and unknown subjects of a problem.
What are the Advantages of Using Correlational Research for an Experiment?
There are several reasons why you can use a correlational study for conducting an experiment. Some of the reasons are mentioned below:
1. Gives Conclusive Results
For an experiment, if you use precise variables by knowing their relationships, you can ace the milestones. It helps you mould the shape of an experiment as per your choice and become easy to conduct it. For example, you may have to study two natural phenomena through experimentation. When you have zero ideas about the selected phenomenon, there are great chances of ending up with nothing. Also, you may require a long time to perform an experiment. For the same task, when you do correlational research, it helps you understand the core concept with all the logic linked with it. This research helps you determine the dependency or independency of one natural phenomenon on the other one.
2. Controlled Experiments
When conducting an experiment, you can go two ways. One of the ways is controlled environments of an experiment, while the other one is uncontrolled environments. In the case of an uncontrolled environment of the experiment, you do not have to set any conditions. Here, things and settings remain natural. Also, you may not have to control the variables of research.
On the other hand, the controlled experiments are completely different from the uncontrolled ones. In this type of experiment, you have to see multiple aspects. It includes dependent, independent and constant variables. Furthermore, it includes a control group as per the need of the hour. Here, you cannot make any selection randomly, but there must be a logical connection between each step. It is correlational research that provides an effective reason to define the categories of variables.
3. Relation of Variables
With correlational research, you can explore the relationships of variables. From a broader perspective, you can get to know about three main correlations as given below:
- Zero correlation: whenever a research study shows you that there is no relation between selected variables, it means zero correlation exists between them.
- Positive correlation: when conducting research, you can also find a positive correlation between variables. In a positive correlation, you can see that the change relation is direct. Suppose one variable is increasing in value. In positive correlation, the second variable will also increase at the same rate.
- Negative correlation: at the time of finding a relationship between different variables, you may find that the change in one variable is opposite to the change in other variables. In simple words, when there is an inverse relationship between the change of variable, this type of correlation is termed a negative correlation of research.
At the time of designing an experiment, all of the three above-mentioned relations help you very well. There can be different purposes for conducting an experiment for these three relations. Mostly Researchers may feel reluctant to do the experiment when there is zero correlation, or they may go for it as per the need of the hour. Similarly, when the case is about positive or negative correlation, it is frequently used to design an experiment for achieving the objectives.
4. Designing a Hypothesis for an Experiment
At the time of designing an experiment, correlational research works well to generate a hypothesis. Without a hypothesis, you cannot set the base of an experiment. Now, coming up with an effective hypothesis is no less than a challenge. A compelling hypothesis has three main parts, which include; expectation related to the experiment, an expectation of result and the logical importance of the hypothesis. Making a hypothesis is not an easy task, but you have to work as per the if-then-because statement. If you fail in any one aspect from if-then-because, then you may not be able to conduct a good experiment. It is correlational research which paves the path to success and helps you generate a logical hypothesis.
Furthermore, it is a hypothesis of an experiment which defines the controlling factor and helps you meet the defined results of the study. If you find it difficult to use correlational research for generating hypotheses, you can avail cheap dissertation writing services. In this way, you can better ensure a reliable experiment.
Final Thoughts
First of all, you have to be clear that you can use the results obtained from a correlational study to design an experiment. The above-mentioned points help you understand the importance of correlational research for designing an experiment. Read and understand each pointer by grasping the core points. Based on the type and purpose of the experiment, you can identify if it is necessary to go for the research of correlation. Some of the experiments may not need a correlation study because of the simplicity of the procedure. Also, there can be chances that the information you need for an experiment is already available to you. That’s why you have to be careful about several aspects and find the need for a correlation study.
