Welcome to Lab!

Intermediate and Advanced Laboratory, at their core, are about the making and supporting of scientific claims using modern data acquisition techniques and error analysis software. Scientists must have the abilities to analyze data, make conclusions, and then re-test those conclusions.

While honing these skills, Intermediate Lab will introduce you to modern experimental techniques in many physical disciplines, including: high energy physics, optics, plasma physics, nuclear and atomic physics, and much more.

As previously stated, you will be responsible for making scientific claims and verifying them by analyzing data that you will take. The importance of error analysis cannot be overstated. Many physicists spend much of their careers analyzing error margins and discussing their significance. So what is an "error"?

What is Error?

Errors come in two flavors, systematic and random. When making a scientific claim you must address the confidence in your claim through the analysis of both kinds of errors.

When students arrive at an experimental measurement it is often compared to a "known" value. (This process is often cleverly disguised as "percent error") The discrepancy between an accepted (or known) value and a measurement is not a "true" error because the accepted value is itself a measurement complemented by a confidence in its value. All measurements are made by humans, and therefore rely on man-made instruments and our own perceptive capabilities.

How then can we decide what is a significant error and what is negligible? When we begin the grueling task of error analysis, what should we consider in order to present a faithful interpretation of our data? It is your job to identify and quantitatively decide which errors to consider. For example, we may consider the incidental vibration caused by a hyper-active lab partner as "garbage data," and thusly remove it, but what about vibrations caused by the not-so-obvious heavy equipment digging up Linn Street? The answers to these questions are often left to the discretion of the individual scientist, and may jar the previously held belief that science is wholly objective. Science is, however, incredibly useful and successful, as you will see during this semester.

Systematic Error

A systematic error is just that: an error that is present throughout an entire data set that biases data in a particular direction. Often systematic errors are the result of an improper calibration, error in a theory, or simply faulty experimental technique.

Attempts must be made to remove systematic error from you data. This may be as simple as recalibrating your device, or as difficult as creating a new theory. In fact, analysis of systematic error is the bridge between experimental and theoretical science.

Random Error

Random error is a kind of error that cannot be eliminated. It is a manifestation of the true limitations of our equipment and senses. However, it is important to note that random error can be reduced. This is commonly seen in experiments reporting things like the speed of light. When we say we know its value to within 6 digits that is simply saying that the random error in our measurement is so small that it is a fluctuation at one-millionth of the entire value, thus yielding a useful number, albeit with random error.