Do you know how to analyze?

Analyzation is one of the cornerstones of the scientific community.

If you’ve been through grade school here in the United States, you may have studied and performed analysis.

If you work in an office, you probably hear the word daily.

What exactly does this word mean, and why is it important to the scientific process?

We’ve created this article to address these questions. You’ll explore the what and how of data analysis, as well as why it’s important within the scientific community.

Ready to get down to brass tacks?

Let’s go.

 

What Does It Mean to Analyze Data?

We must define “analyze” as a word before we begin to perform it on a scientific level. To analyze something means to examine that thing with the purpose of evaluating it.

Although this analyze definition isn’t unique to the scientific community, it’s a great place to start.

By studying something and learning something from it, you gain information through the process. That’s analysis. No matter what field you are studying, the object of your analysis is known as the data.

This theoretical object of your analysis could very well be anything. Within the scientific community, what you are studying is known as scientific data. Scientific data is data collected for the express purpose of study and analysis.

You can analyze peoples’ body language and facial expressions, discerning how they feel based on what you see.

You can analyze charts and graphs by reading the information on them and coming to a conclusion based on that information.

All of this is data analysis. However, scientific analysis of scientific data requires you to study results from the process of experimentation.

 

How to Analyze Data in a Comprehensive Scientific Manner

It’s one thing to analyze the data that you receive from someone’s body language and be able to tell how someone is feeling. It’s quite another to perform a scientific analysis.

Once you begin to comprehend the data before you, you can begin a scientific data analysis. This is a process that’s pretty uniform across the board, regardless of your field of research.

Check out the steps outlined below to make sure you’re analyzing in a truly scientific manner.

 

1. Look for Errors in the Data

Don’t believe everything you read. Or see. Especially when it comes to new data brought forth by new experiments.

You must check for any possible errors that could have occurred in the experiment or in the collection of the data.

Study the experiment closely and notice if any bias could have affected in the process of the experiment to detract from its accuracy.

 

2. Calculating Trends and Averages

A standard way of analyzing data in the world of science is to make calculations based on your data and organize them into charts and graphs.

For example, say you are analyzing data from an experiment in which a placebo was tested against a real medicine in 2 groups of 25 people.

You could discern who was cured and who was not, discovering trends within the experiment along the way. For instance, you may notice that the medicine helped people over 65, but not people younger than that.

You could then discover the average age of the person who reacted to the medicine in the experiment. From there, you would make your charts and graphs.

 

Presenting Data to the Scientific Community: Why We Need to Analyze

Science is something that is performed everywhere, by everyone. By analyzing scientific data, you provide the community with the necessary information to come to new understandings.

There have been certain scientific discoveries which have led to inventions that have impacted the entire world, like electricity and automobiles.

It is vital to the very idea of progress that these discoveries be shared with the world.

On a different level, your own scientific community plays an important role in the scientific process:

  • Evaluation: Once you present your data analysis to the community, they will take time to review and evaluate it. It is important the data be presented to the community for them to identify flaws in the idea or the experimentation process, as well as possible errors in outcome.
  • Criticism: The community will provide criticism, helping eliminate the risk of fraud and bias in experiments. Peer review and approval are vital in order for data to be generally accepted as fact.
  • Support: Other scientists provide support, recognition, and esteem. This motivates people to work hard in their fields and make breakthroughs and advancements in the scientific world.
  • Ideas: When one scientist reads the data analysis of another, he or she may have ideas in a new field. Constant contact and review keep the field fresh and the innovations flowing.

 

Analyze to Further Science and Support the Community

By analyzing scientific data and presenting it to the community, you aren’t just helping yourself and your own reputation.

You’re helping build the platform which future generations will stand upon, and providing a base of ideas that will light the way for those that come after you.

Pin It on Pinterest

Share This