A human mind is a powerful tool that allows you to sift through seemingly unrelated variables and establish a connection with regards to a specific subject at hand. This skill is what comes to play when we talk about correlational research.

Correlational research is something that we do every day; think about how you establish a connection between the doorbell ringing at a particular time and the milkman’s arrival. As such, it is expedient to understand the different types of correlational research that are available and more importantly, how to go about it.

**What is Correlational Research? **

Correlational research is a type of research method that involves observing two variables in order to establish a statistically corresponding relationship between them. The aim of correlational research is to identify variables that have some sort of relationship do the extent that a change in one creates some change in the other.

This type of research is descriptive, unlike experimental research that relies entirely on scientific methodology and hypothesis. For example, correlational research may reveal the statistical relationship between high-income earners and relocation; that is, the more people earn, the more likely they are to relocate or not.

**What are the Types of Correlational Research?**

Essentially, there are 3 types of correlational research which are positive correlational research, negative correlational research, and no correlational research. Each of these types is defined by peculiar characteristics.

**Positive Correlational Research**

Positive correlational research is a research method involving 2 variables that are statistically corresponding where an increase or decrease in 1 variable creates a like change in the other. An example is when an increase in workers’ remuneration results in an increase in the prices of goods and services and vice versa.

**Negative Correlational Research**

Negative correlational research is a research method involving 2 variables that are statistically opposite where an increase in one of the variables creates an alternate effect or decrease in the other variable. An example of a negative correlation is if the rise in goods and services causes a decrease in demand and vice versa.

**Zero Correlational Research**

Zero correlational research is a type of correlational research that involves 2 variables that are not necessarily statistically connected. In this case, a change in one of the variables may not trigger a corresponding or alternate change in the other variable.

Zero correlational research caters for variables with vague statistical relationships. For example, wealth and patience can be variables under zero correlational research because they are statistically independent.

Sporadic change patterns that occur in variables with zero correlational are usually by chance and not as a result of corresponding or alternate mutual inclusiveness.

Correlational research can also be classified based on data collection methods. Based on these, there are 3 types of correlational research: Naturalistic observation research, survey research and archival research.

**What are the Data Collection Methods in Correlational research?**

Data collection methods in correlational research are the research methodologies adopted by persons carrying out correlational research in order to determine the linear statistical relationship between 2 variables. These data collection methods are used to gather information in correlational research.

The3 methods of data collection in correlational research are naturalistic observation method, archival data method, and the survey method. All of these would be clearly explained in the subsequent paragraphs.

**Naturalistic Observation**

Naturalistic observation is a correlational research methodology that involves observing people’s behaviors as shown in the natural environment where they exist, over a period of time. It is a type of research-field method that involves the researcher paying closing attention to natural behavior patterns of the subjects under consideration.

This method is extremely demanding as the researcher must take extra care to ensure that the subjects do not suspect that they are being observed else they deviate from their natural behavior patterns. It is best for all subjects under observation to remain anonymous in order to avoid a breach of privacy.

The major advantages of the naturalistic observation method are that it allows the researcher to fully observe the subjects (variables) in their natural state. However, it is a very expensive and time-consuming process plus the subjects can become aware of this act at any time and may act contrary.

**Archival Data**

Archival data is a type of correlational research method that involves making use of already gathered information about the variables in correlational research. Since this method involves using data that is already gathered and analyzed, it is usually straight to the point.

For this method of correlational research, the research makes use of earlier studies conducted by other researchers or the historical records of the variables being analyzed. This method helps a researcher to track already determined statistical patterns of the variables or subjects.

This method is less expensive, saves time and provides the researcher with more disposable data to work with. However, it has the problem of data accuracy as important information may be missing from previous research since the researcher has no control over the data collection process.

**Survey Method**

The survey method is the most common method of correlational research; especially in fields like psychology. It involves random sampling of the variables or the subjects in the research in which the participants fill a questionnaire centered on the subjects of interest.

This method is very flexible as researchers can gather large amounts of data in very little time. However, it is subject to survey response bias and can also be affected by biased survey questions or under-representation of survey respondents or participants.

These would be properly explained under data collection methods in correlational research.

**Examples of Correlational Research**

Correlational research examples are numerous and highlight several instances where a correlational study may be carried out in order to determine the statistical behavioral trend with regards to the variables under consideration. Here are 3 case examples of correlational research.

- You want to know if wealthy people are less likely to be patient. From your experience, you believe that wealthy people are impatient. However, you want to establish a statistical pattern that proves or disproves your belief. In this case, you can carry out correlational research to identify a trend that links both variables.
- You want to know if there’s a correlation between how much people earn and the number of children that they have. You do not believe that people with more spending power have more children than people with less spending power.

You think that how much people earn hardly determines the number of children that they have. Yet, carrying out correlational research on both variables could reveal any correlational relationship that exists between them.

- You believe that domestic violence causes a brain hemorrhage. You cannot carry out an experiment as it would be unethical to deliberately subject people to domestic violence.

However, you can carry out correlational research to find out if victims of domestic violence suffer brain hemorrhage more than non-victims.

**What are the Characteristics of Correlational Research?**

**Correlational Research is non-experimental**

Correlational research is non-experimental as it does not involve manipulating variables using a scientific methodology in order to agree or disagree with a hypothesis. In correlational research, the researcher simply observes and measures the natural relationship between 2 variables; without subjecting either of the variables to external conditioning.

**Correlational Research is Backward-looking**

Correlational research doesn’t take the future into consideration as it only observes and measures the recent historical relationship that exists between 2 variables. In this sense, the statistical pattern resulting from correlational research is backward-looking and can seize to exist at any point, going forward.

Correlational research observes and measures historical patterns between 2 variables such as the relationship between high-income earners and tax payment. Correlational research may reveal a positive relationship between the aforementioned variables but this may change at any point in the future.

**Correlational Research is Dynamic**

Statistical patterns between 2 variables that result from correlational research are ever-changing. The correlation between 2 variables changes on a daily basis and such, it cannot be used as a fixed data for further research.

For example, the 2 variables can have a negative correlational relationship for a period of time, maybe 5 years. After this time, the correlational relationship between them can become positive; as observed in the relationship between bonds and stocks.

- Data resulting from correlational research are not constant and cannot be used as a standard variable for further research.

**What is the Correlation Coefficient?**

A correlation coefficient is an important value in correlational research that indicates whether the inter-relationship between 2 variables is positive, negative or non-existent. It is usually represented with the sign [r] and is part of a range of possible correlation coefficients from -1.0 to +1.0.

The strength of a correlation between quantitative variables is typically measured using a statistic called Pearson’s Correlation Coefficient (or Pearson’s r). A positive correlation is indicated by a value of 1.0, a perfect negative correlation is indicated by a value of -1.0 while zero correlation is indicated by a value of 0.0.

It is important to note that a correlation coefficient only reflects the linear relationship between 2 variables; it does not capture non-linear relationships and cannot separate dependent and independent variables. The correlation coefficient helps you to determine the degree of statistical relationship that exists between variables.

**What are the Advantages of Correlational Research?**

- In cases where carrying out experimental research is unethical, correlational research can be used to determine the relationship between 2 variables. For example, when studying humans, carrying out an experiment can be seen as unsafe or unethical; hence, choosing correlational research would be the best option.
- Through correlational research, you can easily determine the statistical relationship between 2 variables.
- Carrying out correlational research is less time-consuming and less expensive than experimental research. This becomes a strong advantage when working with a minimum of researchers and funding or when keeping the number of variables in a study very low.
- Correlational research allows the researcher to carry out shallow data gathering using different methods such as a short survey. A short survey does not require the researcher to personally administer it so this allows the researcher to work with a few people.

**What are the Disadvantages of Correlational Research?**

- Correlational research is limiting in nature as it can only be used to determine the statistical relationship between 2 variables. It cannot be used to establish a relationship between more than 2 variables.
- It does not account for cause and effect between 2 variables as it doesn’t highlight which of the 2 variables is responsible for the statistical pattern that is observed. For example, finding that education correlates positively with vegetarianism doesn’t explain whether being educated leads to becoming a vegetarian or whether vegetarianism leads to more education.
- Reasons for either can be assumed, but until more research is done, causation can’t be determined. Also, a third, unknown variable might be causing both. For instance, living in the state of Detroit can lead to both education and vegetarianism.
- Correlational research depends on past statistical patterns to determine the relationship between variables. As such, its data cannot be fully depended on for further research.
- In correlational research, the researcher has no control over the variables. Unlike experimental research, correlational research only allows the researcher to observe the variables for connecting statistical patterns without introducing a catalyst.
- The information received from correlational research is limited. Correlational research only shows the relationship between variables and does not equate to causation.

**What are the Differences between Correlational and Experimental Research?**

**Methodology**

The major difference between correlational research and experimental research is methodology. In correlational research, the researcher looks for a statistical pattern linking 2 naturally-occurring variables while in experimental research, the researcher introduces a catalyst and monitors its effects on the variables.

**Observation**

In correlational research, the researcher passively observes the phenomena and measures whatever relationship that occurs between them. However, in experimental research, the researcher actively observes phenomena after triggering a change in the behavior of the variables.

**Causality**

In experimental research, the researcher introduces a catalyst and monitors its effects on the variables, that is, cause and effect. In correlational research, the researcher is not interested in cause and effect as it applies; rather, he or she identifies recurring statistical patterns connecting the variables in research.

**Number of Variables**

research caters to an unlimited number of variables. Correlational research, on the other hand, caters to only 2 variables.

- Experimental research is causative while correlational research is relational.
- Correlational research is preliminary and almost always precedes experimental research.
- Unlike correlational research, experimental research allows the researcher to control the variables.

**How to Use Online Forms for Correlational Research**

One of the most popular methods of conducting correlational research is by carrying out a survey which can be made easier with the use of an online form. Surveys for correlational research involve generating different questions that revolve around the variables under observation and, allowing respondents to provide answers to these questions.

Using an online form for your correlational research survey would help the researcher to gather more data in minimum time. In addition, the researcher would be able to reach out to more survey respondents than is plausible with printed correlational research survey forms.

In addition, the researcher would be able to swiftly process and analyze all responses in order to objectively establish the statistical pattern that links the variables in the research. Using an online form for correlational research also helps the researcher to minimize the cost incurred during the research period.

To use an online form for a correlational research survey, you would need to sign up on a data-gathering platform like Formplus. Formplus allows you to create custom forms for correlational research surveys using the Formplus builder.

You can customize your correlational research survey form by adding background images, new color themes or your company logo to make it appear even more professional. In addition, Formplus also has a survey form template that you can edit for a correlational research study.

You can create different types of survey questions including open-ended questions, rating questions, close-ended questions and multiple answers questions in your survey in the Formplus builder. After creating your correlational research survey, you can share the personalized link with respondents via email or social media.

Formplus also enables you to collect offline responses in your form.

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**Conclusion**

Correlational research enables researchers to establish the statistical pattern between 2 seemingly interconnected variables; as such, it is the starting point of any type of research. It allows you to link 2 variables by observing their behaviors in the most natural state.

Unlike experimental research, correlational research does not emphasize the causative factor affecting 2 variables and this makes the data that results from correlational research subject to constant change. However, it is quicker, easier, less expensive and more convenient than experimental research.

It is important to always keep the aim of your research at the back of your mind when choosing the best type of research to adopt. If you simply need to observe how the variables react to change then, experimental research is the best type to subscribe for.

It is best to conduct correlational research using an online correlational research survey form as this makes the data-gathering process, more convenient. Formplus is a great online data-gathering platform that you can use to create custom survey forms for correlational research.

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## FAQs

### What are the examples of correlational research design? ›

**If there are multiple pizza trucks in the area and each one has a different jingle, we would memorize it all and relate the jingle to its pizza truck**. This is what correlational research precisely is, establishing a relationship between two variables, “jingle” and “distance of the truck” in this particular example.

**What are the different types of correlational research methods? ›**

There are three types of correlational research: **naturalistic observation, the survey method, and archival research**.

**What is an example of a research question for a correlational study? ›**

For example, if you asked: **Is there a significant positive correlation between age and the job satisfaction of ice cream shop employees?** Your null hypothesis would be: There is no significant positive correlation between age and the job satisfaction of ice cream shop employees.

**What is an example of correlational design in psychology? ›**

For example, let's say that **“marriage” has a negative correlation with “cancer,” meaning that people who are married are less likely to develop cancer throughout their lives than those who remain single**. This doesn't necessarily mean that one causes the other or that marriage directly avoids cancer.

**What are the types of correlation with example? ›**

Correlation coefficient | Type of relationship | Levels of measurement |
---|---|---|

Point-biserial | Linear | One dichotomous (binary) variable and one quantitative (interval or ratio) variable |

Cramér's V (Cramér's φ) | Non-linear | Two nominal variables |

Kendall's tau | Non-linear | Two ordinal, interval or ratio variables |

**Which is the best example of a correlation? ›**

A basic example of positive correlation is **height and weight**—taller people tend to be heavier, and vice versa. In some cases, positive correlation exists because one variable influences the other. In other cases, the two variables are independent from one another and are influenced by a third variable.

**What is a correlational design method? ›**

A correlational research design **investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them**. It's a non-experimental type of quantitative research.

**How many main methods are there to find out the correlation? ›**

There are three types of correlation coefficients and they are as follows: Pearson correlation: This correlation measures the linear relationship between two variables. That said, it can't tell the difference between independent and dependent variables.

**What are examples of correlational research in healthcare? ›**

Examples of correlational studies would be **studies that examine the relationship between age and cholesterol level or between dose of Lisinopril and blood pressure**. Common statistical methods used in this type of study are Pearson correlation, chi-square, and regression.

**How do you solve correlation questions? ›**

The correlation coefficient can be calculated by **first determining the covariance of the given variables.** **This value is then divided by the product of standard deviations for these variables**.

### What is the best sampling method for correlational research? ›

**Stratified sampling** allows researchers to choose subjects based on specific characteristics, such as gender or race in correlational research. This helps ensure that each case represents the population.

**What is an example of correlational research in social psychology? ›**

Social psychologists use correlational research to look for relationships between variables. For example, social psychologists might carry out a correlational study **looking at the relationship between media violence and aggression**.

**What is the most common type of correlation research? ›**

**The survey method** is the most common method of correlational research; especially in fields like psychology. It involves random sampling of the variables or the subjects in the research in which the participants fill a questionnaire centered on the subjects of interest.

**What is a real life example of correlation? ›**

Common Examples of Positive Correlations

The more time you spend running on a treadmill, the more calories you will burn. The longer your hair grows, the more shampoo you will need. The more money you save, the more financially secure you feel. As the temperature goes up, ice cream sales also go up.

**What is the most common type of correlation? ›**

**Pearson's correlation**: This is the most common correlation method. It corresponds to the covariance of the two variables normalized (i.e., divided) by the product of their standard deviations.

**Is Regression a correlational research design? ›**

**Regression is indeed correlational in the broad sense**, as has already been said here, but the strictest, most simplistic sense of correlational may appeal to those who have a less nuanced understanding of general linear models.

**What is the easiest method to find correlation between two variables? ›**

**Using a scatterplot**, we can generally assess the relationship between the variables and determine whether they are correlated or not. The correlation coefficient is a value that indicates the strength of the relationship between variables. The coefficient can take any values from -1 to 1.

**What is correlation and its methods of measurement? ›**

Correlation is **a statistical measure that expresses the extent to which two variables are linearly related** (meaning they change together at a constant rate). It's a common tool for describing simple relationships without making a statement about cause and effect.

**What are the six main research methods? ›**

In conducting research, sociologists choose between six research methods: **(1) survey, (2) participant observation, (3), secondary analysis, (4) documents, (5) unobtrusive measures, and (6) experiments**.

**What are the 4 main types of research? ›**

There are four main types of Quantitative research: **Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research**. attempts to establish cause- effect relationships among the variables.

### What formula is used in correlational research? ›

Pearson correlation

mx and my are the means of x and y variables. the p-value (significance level) of the correlation can be determined : by using the correlation coefficient table for the degrees of freedom : df=n−2. or by calculating the t value : **t=r√1−r2√n−2**.

**How do you determine a correlation relationship? ›**

The correlation coefficient is measured on a scale that varies from + 1 through 0 to – 1. Complete correlation between two variables is expressed by either + 1 or -1. **When one variable increases as the other increases the correlation is positive; when one decreases as the other increases it is negative**.

**How do you find correlation from data? ›**

Use the formula (z_{y})_{i} = (y_{i} – ȳ) / s _{y} and calculate a standardized value for each y_{i}. Add the products from the last step together. Divide the sum from the previous step by n – 1, where n is the total number of points in our set of paired data. The result of all of this is the correlation coefficient r.

**What are the two most popular types of correlational studies? ›**

There are three main types of correlational studies: **natural observation**, survey research, and archival research. It's important to remember that although correlational research can suggest a relationship between variables, it CANNOT prove that one variable causes a change in another variable.

**What is descriptive correlational research design? ›**

Descriptive Correlational Designs. Descriptive correlational studies **describe the variables and the relationships that occur naturally between and among them**. Predictive Correlational Designs. Predictive correlational studies predict the variance of one or more variables based on the variance of another variable (s).