Purpose

The purpose of this project writeup is for you to practice technical commumication, particularly the use of concise descriptive text and figures. Good technical writing requires a set of skills different from your high school English class, so expect this to require practice and some hard work.

In particular, figures are essential in technical writing. If you’ve done a good job, a reader should be able to understand your experiment and results just by looking at the figures and graphs.

Your project writeup should be a OneDrive document (either PDF or Word document) containing the following sections:

Introduction

The introduction should give a brief description of what you’re trying to measure, and list the questions you hope to answer with your measurements.

Common mistakes

  • Forgetting your names at the top of the document.
  • Failing to precisely explain what you’re doing. If you’re measuring a freezer, you’re not just measuring “a freezer”; you’re measuring a specific freezer. Give the relevant information such as how the compartments are laid out, the model number, or any settings it has.

Experimental setup

The next section should explain your experimental setup. Photographs, diagrams, and schematics help immensely here; paragraphs of flowery English generally do not. Your goal is to communicate enough that another student team could read what you’ve written and reproduce your results.

Common mistakes

  • Explaining with words what is better communicated in graphical form. If any of your text can be replaced with a table, schematic, photograph, diagram, or plot, then do it!

  • Leaving out important information necessary to reproduce what you did.

  • Not controlling for things that are easy to control for. Make sure you’re using equal volumes or masses when comparing things. If you’re heating up multiple samples, heat them up to the same temperature. You can’t control for everything, but do what you can.

  • Not logging enough data. Think about what sorts of timescales you’re working with, and measure appropriately. A refrigerator cycles on and off for tens of minutes, so you probably need to watch it for several hours at minimum. If you’re cooking something, cook it all the way. If you’re letting something cool, let it get down to room temperature.

Figures

Include one or more figures showing the data you collected. Each figure should have a caption explaining what the figure is showing.

Your figures should be created with Python/Matplotlib (not Excel/Google sheets/whatever). Make sure to label your axes, use reasonable units, and use a legend where appropriate.

Consider adding information to the figures to provide context. For example, if you’re boiling or freezing water, add a line on the plot to show the boiling or freezing point. If events occur at particular times (opening a fridge door, taking something off the stove, etc), add a vertical line or annnotation mark to indicate this; don’t just describe it in text.

Common mistakes

  • Making multiple plots when one is sufficient. If you want to compare data (and usually we do!) then put them on the same plot. If the plots obscure each other, consider plotting with thinner lines, showing just the data points, or using transparency.

  • Leaving out key information necessary to interpret the plot. If you moved a sensor during the experiment, took a pot off the stove, etc., then note that on the plot. Your reader shouldn’t have to jump back and forth between plot and text to understand what’s happening.

  • Plotting data gaps. If there are gaps in your data, matplotlib will just just “connect the dots” by default, leaving the impression of large linear transitions when in fact there is no data. If this is the case, consider using multiple plot commands to just plot the continuous segments, or explicitly plot the data points and not just the connecting line.

  • Using unhelpful time scales, such as measuring an hours-long experiment in seconds. Think about the most natural unit your mind uses to talk about this time scale, and use that (for example, you would never say, “I’ll be there in 300 seconds.”)

Analysis

The analysis section should discuss your observations and what you learned from the data. These needn’t be hard scientific conclusions, but do explain what you can infer from the data and discuss anything you found surprising or noteworthy. Did your measurements match your expectations?

Common mistakes

  • Not commenting on anomolous data. It’s ok if weird or unexplainable things show up in your data, but don’t ignore these! If your temperature sensor says it’s 50F in the freezer, comment on this!

  • Making claims that aren’t supported by the data. It’s ok to say that the data are inconclusive, or that other factors may have influenced your measurements.

Evaluation of experimental setup

Please include a few sentences analyzing your experimental setup. If you had it to do over again, what would you do differently? Is there anything you wish you had? Are there different sensors or other items we should try to purchase for next year’s students?

Code and data

You should make sure that your code is copied to OneDrive. Please give the files meaningful names so we know what is what.

Your data should also be in OneDrive.