We all know what Research is, don’t we? There is research happening in every walk of life, everyday. When a group of scientists make a breakthrough in coming up with a medicine, they are conducting research. Similarly, when an organization like World Bank comes up with a white paper on the economic impact of a pandemic, they too have conducted research. These examples may not seem to share a lot in common, but at the core they both are outcomes of a research exercise.
In this post we will uncover the world of research and open it up for a deep dive over many other posts on the process of research, and best practices associated with it.
In this post, let’s answer the question that we started out with – What is research?
People look for answers to problems around them. We have a problem with pollution, we look for transport and power solutions that don’t rely on fossil fuels. We have a problem with the COVID pandemic, we look for answers in vaccines.
At its simplest, research can be defined as:
A systemic process that leads to new knowledge and understandingPaul D. Leedy • Jeanne Ellis Ormrod – ‘Practical Research
Planning and Design, 12th ed’
Researchers typically follow a systemic process to get to the answers they are looking for. It’s not written in stone nor is standardized. Unless you have a prior background in research, the process may come across as daunting. What follows tries to simplify the explanation of the process. Note that this is only an introduction and does not
1. Start with Observations
The process of research starts with a researcher observing something around them that gets them curious to dig deeper. It could be a phenomenon, a trend, or something fundamental like in the case of Newton noticing the fall of an apple from the tree.
Obviously, not every observation is as impactful. Researchers are also human, and they have a few areas of interest in which they are more sensitive and make a note of their observations. When the researcher observes something in the real world in their area of interest, they try to explain it with a known theory.
Example: An apple falls down from the tree, and you shed light on the gravitational force that is acting on that apple.
However, at times existing theory is not sufficient to explain an observation.
2. Come up with a Hypothesis
When existing theory fails to fully answer an observation, researcher comes up with a possible explanation – we call this a Hypothesis. A hypothesis is just that, it’s just a possibility waiting to be proven.
Earth may have a magnetic force that is pulling the apple down
Coming up with a Hypothesis can get tricky. Researcher may need to spend time reading on the topic to see if there is existing theory explaining the observation. Also a hypothesis should be testable with data. It can’t be an opinion that we pass casually.
3. Collect data
This is generally the most tiring part of the whole process. The data collected should be good enough to serve as an evidence to prove the research outcome. It could be qualitative, quantitative, primary, secondary sources, firsthand observations, depending on the topic at hand. You could use various methods to collect data – interviews, experiments, literature, and our favorite – Surveys!
The data collection part may seem like a straightforward job, but is the most complicated part of the entire research process. However, thanks to many a researchers who contributed significantly to the topic of our interest, you generally have a body of knowledge out there to be tapped to get you started.
Even Newton had help from the likes of Aristotle, Yajnavalkya, Galileo, and Copernicus.Microsoft Word – Cappi Alberto 1 May14 K1.doc (cultureandcosmos.org)
Satapatha Brahmana Part IV (SBE43): Eighth Kâ<I>n</I><I>d</I>a: VIII, 7, 3. Third Brâhma<I>n</I>a (sacred-texts.com)
4. Analyze data looking for answers
Depending on the type and variety of data collected, various analytic techniques can be applied. Starting from preparing the data for analysis – cleaning, validating it, to drawing inferences and insights, the process involves significant statistical and mathematical acumen. At times, you may have to reject the data and go back to collecting it again.
It is important to know what techniques are suitable for the data collected. Random application of these techniques with little or no background in statistics could be deadly.
Additionally, analysis and bias don’t go hand in hand. It’s important to keep an eye on bias from the time you collect data, to the time of analyzing and drawing inferences.
5. Presenting Research Outcomes
This is where you go public with your research, so better be thorough with the whole process that led you to the outcome. At times it requires courage to present the findings, but as long as they are backed by a thorough process you should be good. At least, people won’t be as hostile as they were towards Galileo.
Research Outcomes should be presented keeping the context of the consumers of the research in mind. It could be the sponsors, public at large or other stakeholders. It’s important to not just share the raw findings, but include the process followed, data collected (if appropriate), and the analytic techniques employed so as to instill confidence in the Researcher’s work.
Like we said earlier, this is just an introduction to the world of Research, a tip of the iceberg, but it should help you get started on your own path of data driven decision making. At least, it should not look as daunting a task. How do you go about doing your own Research? Here’s help.
As next steps you my want to do the following:
- Connect with a topic that interests you to dig into.
- Come up with a set of questions that need to be answered.
- Frame a Research hypothesis for you to begin your own Research journey.
- Collect data from the sources you have access to.
- Analyze it looking for inconsistencies, in addition to insights.
- Share what you discover, and help the world around you.
All the best!