Scientific Investigations: Data, Evidence & Reasoning

Instructor: David Wood

David has taught Honors Physics, AP Physics, IB Physics and general science courses. He has a Masters in Education, and a Bachelors in Physics.

What is a scientific investigation? And how are data, evidence, and reasoning central to the scientific process? Learn about the difference between data and evidence and why logical reasoning is just as necessary as data itself.

Understanding Scientific Investigations

One day you're having a conversation with a friend, and that friend tells you a story. They say, 'I got sick just a few hours after I touched the bubble wrap. So for your own sake, stay away from the stuff.'

It's fair to say that most people would think that suggestion was ridiculous and probably ignore it. Yet, people make conclusions that are just as preposterous every day. A better understanding of science would help reduce these kinds of conclusions.

Science is the study of the natural world through the collection and analysis of empirical data. It's a process that leads us to a better understanding of the world. A scientific investigation is how scientists use the scientific method to collect the data and evidence that they plan to analyze.

Overview of the Scientific Method
Overview of the scientific method

Scientific investigations rely on empirical data, verifiable evidence, and logical reasoning. They are the heart of the scientific process. Let's take a look at each of these things, talk about what they mean, and learn how they are often misused or underestimated.

Data, Evidence, and Reasoning


Empirical data is facts, numbers, and statistics measured in the real world and collected together for analysis. You could collect data on how many cars of different colors pass through an intersection, at what ages people get diagnosed with prostate cancer, or a million other things.

Data is usually most useful when it is made up of numbers. This is called quantitative data, but you can also have data that is made up of personal accounts and descriptions and other non-numerical information. This is called qualitative data. However, individual accounts and stories do not qualify as data--qualitative information only becomes data when it's put together on a large scale.

It is often said that, 'The plural of anecdote is not data.' This means that your personal experiences have no bearing on what the truth about a subject is--it would take the personal experiences of huge numbers of people before you could make conclusions from them.

The job of scientists is to collect data and use it to explain the world.
The job of scientists is to collect data and use it to explain the world


Evidence is a body of facts and information showing whether a hypothesis is true or untrue. Data forms the basis for evidence, so there's a lot of overlap between the two concepts. However, data is raw information with no judgment attached. Evidence is when data is used to try to prove or disprove a particular point.

So maybe your study of the colors of cars passing through an intersection might be used as evidence to show that the most popular color of car in your neighborhood is dark gray. Or, your data for what ages people get diagnosed with prostate cancer could be used as evidence for the proposition that prostate cancer affects mostly older men. Evidence should always be verifiable--it should be possible to get the same results and make the same conclusions by taking another look at the real world.


Logical reasoning is a part of science that often gets overlooked. When we use data to provide evidence for a particular hypothesis, that hypothesis must make logical sense. If you have an idea that might explain a particular phenomenon in the natural world, it needs to be internally and externally consistent.

For example, you can't argue that dark gray cars are the most popular because people in your neighborhood are particularly unhappy and associate the color with the state of mind if you also argue that black is unpopular because people in your neighborhood are particularly happy. To say that people are both particularly unhappy and particularly happy at the same time is a logical contradiction.

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