Correlational research

What is Correlational research?

Correlational research is a non-experimental research approach where a researcher examines and measures two variables, aiming to analyze and evaluate the statistical connection between them without any influence from external factors.

Correlational research Example

The correlation coefficient provides a statistical measure of the relationship between two variables, ranging from -1 to +1. A value close to +1 indicates a positive correlation, while a value close to -1 indicates a negative correlation. When the correlation coefficient is close to zero, it signifies no relationship between the variables.

To illustrate the concept of correlational research, let’s consider a hypothetical example. Imagine a researcher investigating the correlation between cancer and marriage. In this study, the two variables of interest are the occurrence of the disease and marital status. Let’s assume that the findings reveal a negative correlation between marriage and cancer, suggesting that married individuals are less likely to develop cancer.

However, it is important to note that this correlation does not imply a direct causal relationship between marriage and cancer prevention. In correlational research, determining causality is impossible—what causes what. It is a common misconception that correlational studies only involve quantitative variables. In reality, quantitative and categorical variables can be measured, but no variables are manipulated, regardless of their type.

Types of correlational research

Three primary types of correlational research have been identified:

1. Positive correlation: In this type, an increase in one variable corresponds to an increase in the other variable, and a decrease in one variable corresponds to a decrease in the other variable. For instance, the more money a person has, the more cars they own.
2. Negative correlation: Unlike a positive correlation, a negative correlation occurs when an increase in one variable leads to a decrease in the other variable, and vice versa. For example, higher levels of education might be associated with a lower crime rate. This doesn’t imply that lack of education directly causes crimes but rather suggests that education and crime share a common underlying factor, such as poverty.
3. No correlation: This type of correlation indicates no consistent relationship between the two variables. Changes in one variable do not necessarily result in any noticeable change in the other variable. For instance, being a millionaire and experiencing happiness is not correlated. Increasing wealth does not necessarily lead to increased happiness.

It’s important to note that correlational research does not establish causality, meaning it cannot determine which variable is causing changes in the other. Instead, it focuses on examining and quantifying the relationship between variables.

Characteristics of correlational research

Correlational research exhibits three primary characteristics:

1. Non-experimental: Correlational studies are non-experimental. Researchers do not manipulate variables through a controlled scientific methodology to establish cause-and-effect relationships. Instead, they solely measure and observe the relationship between variables without intervening or subjecting them to external manipulation.
2. Retrospective: Correlational research primarily analyzes historical data and examines past events. Researchers utilize this approach to identify and analyze patterns that existed between two variables in the past. While a correlational study may reveal a positive relationship between variables based on historical data, it is important to recognize that such relationships can change in the future.
3. Dynamic: The patterns observed in correlational research between two variables are not fixed and constant. They are subject to change due to various factors. For example, variables that displayed a negative correlation in the past may exhibit a positive correlation in the future due to changing circumstances or other influences. Correlational relationships are dynamic and can evolve.

It is crucial to understand that correlational research cannot establish causation, predict future outcomes, or explain the observed relationships. Its primary purpose is identifying associations and patterns between variables based on historical data.

Data collection

A key characteristic of correlational research is that the researcher cannot manipulate the variables. Regardless of how or where the variables are measured, the researcher cannot intervene or control them directly. In correlational studies, the researcher primarily observes and measures the variables as they naturally occur or exist. The research can occur in various settings, such as closed environments or public settings, depending on the nature of the studied variables. The focus is on understanding and analyzing the relationship between the variables rather than manipulating them for experimental purposes.

Researchers use two data collection methods to collect information in correlational research.

Naturalistic observation

Naturalistic observation is a data collection method where researchers observe and record the behaviors of individuals in their natural environment, typically without their awareness. This approach falls under the category of field research and can involve observing people in various settings, such as grocery stores, cinemas, playgrounds, or similar places.

Researchers who employ this method aim to be unobtrusive, ensuring that participants remain unaware of being observed to minimize the potential for altering their natural behaviors. Ethically, this approach is deemed acceptable if participant anonymity is maintained and the study is conducted in a public setting where individuals would not reasonably expect complete privacy. For instance, observing people in a grocery store as they select items from aisles and place them in their shopping bags is considered ethically acceptable due to the public nature of such settings.

Naturalistic observation allows for collecting qualitative and quantitative data, depending on the research objectives and the specific behaviors being observed and recorded.

Archival data

Archival data is another approach to correlational research involving using previously collected data from similar research studies. This data is typically obtained through primary research and made available for future analysis.

Contrary to naturalistic observation, working with archival data can be relatively straightforward. For instance, it can involve simple tasks like counting the number of individuals named Richard in different states of America based on social security records.

Using the correlational research method, you can conduct a study to examine the statistical relationship between two variables and uncover valuable insights.

You can make better decisions based on empirical evidence and data by conducting correlational research.