# Guide to Empirical Analysis (With Common Uses and Stages)

By Indeed Editorial Team

Published May 29, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Research involves numerous approaches to analyzing data, including both empirical and subjective methods. Determining how and when to use empirical analysis can help you find practical solutions more efficiently. Understanding this analytical method can also help you establish experiential and provable conclusions about data. In this article, we define empirical analysis, discuss its characteristics, list its applications, and outline each stage of the research process.

## What is empirical analysis?

Empirical analysis is an evidence-based form of research that focuses on verifiable information when interpreting data. Instead of using a theoretical approach to research, an empirical study uses established metrics to inform its results. The root of empiricism is in experiential data that uses concrete examples as proof instead of theoretical ideas.

This analysis approach comprises an important part of the scientific method. For example, the well-established Newtonian laws state that force equals mass multiplied by acceleration. An empirical analysis of this fact involves performing multiple tests to verify the truth behind the concept. Since this type of analysis relies on actual events, it can't supply an absolute solution, only a probability-based response informed by experience.

Read More: How to Write an Analysis (With Importance and Tips)

## Characteristics of empirical analysis

Empirical analysis differs significantly from rationalism and the idea that knowledge originates in intuitive thinking, deduction, and conceptualizing. Empiricism has several identifying characteristics, including:

### Specific research outlines

Empirical studies rely on an established outline that defines the structure of the research. The set format relates to the study's introduction, materials and methodology, results, and discussions (IMRaD). Experiment standardization accommodates the peer review process and improves its value by relying on a proven approach. Each of the stages serves a unique function in the research:

• Introduction: This component refers to background information related to the empirical study. It typically includes the reason for the research and often presents a hypothesis. To lend context to the study, it includes the pertinent details and any relevant assumptions, such as the value of gravity in a physics study.

• Materials and methodology: This aspect of IMRaD describes the methods the study used for testing by listing when and where it took place and how the researchers completed the study. This section details all the materials the test used, such as the type and size of the ball the scientist utilized to test gravity.

• Results: This part of the research process reveals the results. It lists the findings of the study and indicates how the results relate to the hypothesis set out in the introduction.

• Discussions: The final aspect of the empirical analytics outline involves discussing the implications of the study's results. Researchers and reviewers use this section to interpret how to proceed with the data, such as repeating the study in a different location or using a new type of material to perform the same experiment.

### Established research questions

Analyzing data empirically requires clear research questions to inform the study parameters and methodology. Many researchers establish these questions by determining a problem to solve and designing an experiment based on that goal. By establishing a fixed goal, the professional performing the study can come up with a useful hypothesis. Below are the two ways to test a hypothesis:

• Qualitative research: Researchers that use this method rely on language data to interpret the experiences, thoughts, and opinions of the participants. The research may include interviews, focus groups, behavioural observations, and questionnaires with open-ended inquiries.

• Quantitative research: This method involves collecting numerical data to test or affirm a hypothesis. It incorporates methods such as polls, surveys with closed-ended questions, and statistical models that use numerical information to answer a primary question.

Read more: What Is Quantitative Analysis?

### Clearly defined variables

To carry out research using an empirical approach, a study requires clearly defined variables. Scientists declare all the dependent and independent variables that interact with their study. An independent variable is one that the researcher manipulates during the study. A dependent variable is the measurement that changes due to the manipulation of that independent variable. This process is important because it addresses the differences between causation and correlation, thus reducing the risk of bias in the study.

### Explicitly indicated analysis methods

Any empirical study involves full transparency in terms of methodology. Researchers indicate their approach to the study, including the materials, location of the test, and details about the instruments the study may use for measurements. Empirical studies include details related to the collection methods and analysis procedures. They enable the reader to assess the merit of the study by evaluating its reliability and accuracy.

## Common applications for empirical research

There are many applications for empirical studies in the research profession. They enable scientists to control variables while eliminating personal bias. The ability to repeat experimental results adds merit to the studies. Taking a structured approach enables scientists to conduct longitudinal analyses that provide ongoing information about a topic. For instance, empirical analysis is common in physics because scientists can test their theories on a smaller scale. This type of research has many benefits, including:

• Reputability

• Non-biased results

• Ample control over variables

• Flexible designs

## Five-step research cycle

All research, including empirical analyses, undergoes a cycle that facilitates reliable results by using established processes. There is evidence of empiricism as early as 200 BCE, with the Vaisheshika school of philosophy supporting research through the sensory experience. The process evolved over time, with the modern, five-step approach becoming popular in 1969, when the researcher De Groot popularized Aristotle's approach to empirical thinking. The following five steps have become the scientific standard for empirical research:

### 1. Observation

During the observation stage, researchers seek out empirical data using all five senses. Researchers take notes on what they see, the sounds they hear, the smells they observe, the resulting tastes, and all other tactile observations. An example is observing a tree during a temperature shift, where the researcher can monitor and record changes in real-time. The scientist then takes this information and uses it to generate a hypothesis to test with an experiment.

### 2. Induction

Inductive reasoning involves taking specific information and using it to create a generalization. For instance, a scientist can explain observed data using existing knowledge. In the example above, if the researcher notices that the tree smells stronger as the temperature drops, they may use inductive reasoning to produce the following question, "Do trees smell stronger when it gets colder?" A different, unbiased researcher can then conduct an experiment to test the theory by tracking the temperature and the quantity of odour-causing particulate matter in the surrounding air.

Read more: Inductive Reasoning vs. Deductive Reasoning (With Examples)

### 3. Deduction

The deduction stage involves researchers solidifying a hypothesis. This is when general information combines to form a specific conclusion. By using logic and reason to establish a hypothesis for the study, researchers can mitigate bias in the investigation. For instance, consider a study participant who smells the tree's aroma more in the cold even without evidence of a rise in the number of scent particles in the air. This finding suggests that the tree's odour remains the same and that the cold impacts the participant's ability to smell.

Read more: Deductive Reasoning: Definition, Application, and Examples

### 4. Testing

The testing portion of the scientific process relies on the quantitative and qualitative approaches to perform tests. An essential component of empirical studies is repeatability. To remove bias, multiple researchers perform the study without knowledge of the previous results. Repeatedly testing the hypothesis using a statistical analysis of numerical data and qualitative interpretation can determine whether there is sufficient evidence to support the hypothesis.

For example, consider ten repetitions of the study where individuals observe a tree as it gets colder while a scientist monitors the scent particles in the air. If all ten participants notice an increase in the smell and the particulate in the air increases proportionately, the results support the hypothesis that reducing the temperature causes trees to release more odorous particles. Conversely, if all ten participants notice an increase in the smell while there is no measurable increase in particulate matter, it suggests that the participants, rather than the trees, react to the reduction in temperature.

Read more: The 3 Branches of Science and Available Career Options

### 5. Evaluation

In the final step of the empirical research cycle, scientists present their findings, detail any challenges the study posed, and provide a conclusion. During this stage, the researcher acknowledges the limitations they may have faced during the process, such as geographical or seasonal restrictions. To complete the research cycle, the evaluation concludes by providing suggestions for further investigation. For instance, if the study only tested participants during the winter, it may warrant further investigation during the summer months.