In PHYS 331 you will be required to analyze the data that you collect from the online labs. The analysis will involve plotting data (with error bars) and performing weighted fits. In this course, data analysis using Python will be supported.
Python is being support because:
- It is a commonly-used program language in physics research and industry
- It is freely available for anyone to use
You can write and execute Python code using UBC's Open Jupyter Hub. You don't need to install any software, just log in using your CWL.
As an alternative, you can also write and execute Python code using UBC's Jupyter Hub. You don't need to install any software, just log in using your CWL.
If you'd prefer to write and run code on your own system, you can download and install the individual editions of the Anaconda Toolkit.
You can also refer to this set of Python tutorials that demonstrate how to complete some of the common data analysis tasks that you might encounter.
If you prefer, you can complete your data analysis tasks in MATLAB. UBC students are eligible for a free MATLAB license.
Here is a set of MATLAB tutorials. Although you are free to use MATLAB to complete you lab data analysis, MATLAB support from your PHYS 331 instructor/TA will will be very limited/nonexistent.
If you prefer and, if you have access to it, you can complete your data analysis tasks in Maple. Note that UBC does not have a student license for Maple.
Here is a set of Maple tutorials. Although you are free to use Maple to complete you lab data analysis, Maple support from your PHYS 331 instructor/TA will will be very limited/nonexistent.
Note that, to the best of my knowledge, Excel does not easily do weighted fits to data sets. Therefore, in PHYS 331, Excel is generally not a suitable tool for data analysis.
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