Various Forms of Scientific Research

Various forms of Scientific Research can be broadly categorized as follows: Explanatory research, experimentation, Theory, and Reproducibility. Explanatory research involves collecting data and using statistical analysis to interpret it. Experimentation involves identifying patterns in data that can be repeated. The resulting results can be used to test and develop a theory.

Explanatory research

Explanatory research in science is the process of figuring out why things happen. It builds upon a hypothesis by examining variables or collecting data from people in order to explain a phenomenon. This type of research helps increase the general understanding of a topic by exploring it from a variety of perspectives.

Explanatory research aims to understand the cause and effect of events in the past. It does not attempt to control or predict the future. It relies on secondary data collected before the study begins. Often, the data collected is from a different source and does not involve random sampling or allocation.

Explanatory research can be conducted with quantitative or qualitative methods. It can also incorporate case studies or observational data. Its goals depend on the research topic and the budget available. A literature review is an excellent starting point for this type of research. Focus groups and interviews are also great ways to gain information about a particular subject. Pilot studies are another way to obtain funding.


Experimentation is a basic principle in science that allows scientists to quantify a relationship between variables. Often, it is used in pharmacology or toxicology to find the dose-response relationship between new chemicals and disease. In this context, researchers divide a population into groups and then expose each group to different amounts of a chemical or drug. They then compare the responses of the different groups.

Researchers may choose to conduct experiments in various ways, but most studies involve at least one type of controlled experiment. Controlling variables is a key component of any experiment. Controls in scientific research help to determine the variability of a system and check for possible sources of error.


In the context of scientific research, the term “theory” refers to a carefully thought-out explanation of the phenomena observed in nature. These explanations are developed by applying the scientific method. Theories generally make consistent predictions that are supported by a variety of independent strands of evidence. Moreover, they are consistent with the results of previous experiments or other sources of knowledge.

There are two types of scientific theories: hypotheses and models. Hypotheses are descriptive, while models are predictive, but in limited ways. Both kinds of scientific models aim to predict a certain phenomenon. They are used by scientists to advance scientific knowledge and technology.


Many groups, including researchers, journals, funding agencies, and universities, have sought to improve the reproducibility of scientific research. Reproducibility can be improved through the development of robust sharing of data, methodological details, and research materials. Lack of access to these materials, and to the original data and protocols that are often needed, impedes reproducibility. Efforts to improve reproducibility must also include an emphasis on the rigor of the sharing systems.

Reproducibility is a principle that protects the validity of scientific discoveries. During the seventeenth century, reproducibility was the gold standard of scientific research. In that era, only two air pumps were available in England, making it expensive and difficult to create a vacuum. But Dutch scientist Christiaan Huygens was able to build an air pump that created a vacuum, and he traveled to England to demonstrate it. Other early scientists, such as Robert Boyle and Thomas Hobbes, recognized the importance of reproducibility and included a methods section in their scientific papers.

Big data

Big data analysis has become commonplace in the financial and information industries, but it is only recently starting to penetrate the world of medical research. Researchers expect that big data can help them make important discoveries and improve healthcare. According to the Institute of Medicine of the US National Academies of Sciences, “big data is a potentially transformative tool for scientific research”.

However, big data does have its problems. The data derived from big data analyses are often uncontrolled and have a lack of approved quality. As such, most of the scientific hypotheses derived from big data analysis must be followed up with classical scientific studies.

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