Impact of Technology & Math on Science

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.

Learn how technology and mathematics are central to science. Discover examples of how scientists use technology and mathematics for research and communication.

What Are Science and Technology?

When we're at school, everything we learn is separated into subjects: English class, physics class, math, and in some schools even a technology class. But the truth is that everything is related. You might have noticed that technology is everywhere these days, and the same is true of science.

Science is the study of the natural world by following a systematic process of observation, including experiments. Mathematics and technology are tools that scientists use to help them learn about the world.

Technology refers to the devices and inventions that are created through our scientific knowledge. But those devices and inventions can also be used to learn new things in science. Computers can be used analyze data, and satellites can be used to take pictures of the universe and Earth.

Computers are vital to scientific research
Computers are vital to scientific research

And then there's mathematics. Mathematics allows us to put numbers to observations, and to statistically analyze the data we collect to figure out how close it is to the truth. Mathematics can also be used in the form of algebra to provide simple relationships that explain how the world works - such mathematical equations are a constant presence in physics, for example.

In this lesson, we're going to go into a little more detail about how technology and mathematics are used in two key areas: scientific research, and scientific communication.

Scientific Research and Investigations


Technology and mathematics are central parts of scientific research and investigations from start to finish. Computers can be used to collect raw data in a process called data logging. This is where you connect sensors to a computer, and the data that that sensor collects is put straight into that computer, often going directly into plotting a graph. But you can also collect data using specialized technology and equipment like microscopes, telescopes, and simpler devices like stopwatches.

Microscopes are an example of technology being used in science
Microscopes are an example of technology being used in science

Computers can also be used to analyze data once it is collected. Some experiments require months of analysis. For example,the rovers on Mars or particle accelerators like the Large Hadron Collider might collect so much data in a few days that it takes months to analyze. Computers make the process quicker, and practical in the first place. Gone are the days where scientists would sit with a pen and paper doing calculations for whole years of their lives.

The particle accelerator collects large quantities of data
The particle accelerator at CERN collects large quantities of data


Mathematics is also vital to scientific research. Mathematics is involved from the most basic levels like finding averages of all the trials of an experiment, to highly complex algebra like figuring out the laws of physics to explain how the universe is expanding.

Calculations are often central to an investigation, but they can also be the result of investigation. Whenever you investigate how two variables affect each other, it's possible to create a mathematical relationship between them.

Last of all, mathematics is used to calculate something called statistical significance. Statistical significance describes how likely it is that the result you found happened by random chance. It's really important because it represents the quality of your entire study. No drug will be approved for human use if the results were not statistically significant.

So modern scientific research uses both technology and mathematics to great and important effect for everything from collecting data, to analyzing that data, to figuring out the quality of that data. This improves the quality of the science being done, and speeds up how fast it can be completed.

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