Lab Journal Entries
While there isn't complete consistency among sciences or even individual scientists regarding the format of a lab journal, here are some things you'll see in nearly every lab journal entry:
Title
Descriptive of what we were doing, learning
"Lab" or "Physics Lab" are not acceptable. Think more along the lines of "Determining the relationship between air temperature and the speed of sound"
Purpose / guiding question
Why are we doing this experiment? What are we hoping to learn?
Often stated something like, "Purpose: to determine the relationship between _____ and _____ in *yadda yadda yadda* situation.
Go back and re-read your purpose multiple times during your lab. Your procedure, analysis, and conclusion should follow clearly from this statement.
Procedure, equipment
Start to finish, what are you doing to collect the data you'll be analyzing?
In particular, make sure to name and/or describe all equipment used and how you're using it (a labeled diagram might be useful).
All measurements need to be described (what you're measuring, and how you're measuring it).
Good idea to leave a little space for additions, corrections that you make after you start collecting data.
3 isn't the magic number. Not sure where it came from, but this idea that 3 trials of a particular setup, or 3 different values of the independent variable is appropriate for an experiment needs to go! Professional scientists will get as much data as they can to try to get a complete picture. Depending on the experiment, this could be thousands or even millions of data points. We don't have time for that, but 3 data points simply aren't enough to get a broad understanding of the principle at work.
Data, observations
This is where you record all measured values and/or observations you make. Do not include calculations here.
Must be organized, labeled, and include units as appropriate. No "naked numbers"!
Organize data in tables whenever you'll have multiple measurements of the same type.
Analysis
All calculations and graphs go here.
For calculations, show your work for one calculation of each type. For example, you might calculate acceleration from a measured distance, time, and initial velocity 20 times. Show that type of calculation once, then use a table to show just the calculated values you were after. Organize these carefully, and try to match the formatting of the data tables in the previous section.
At a minimum, graph your purpose. If you're looking for the relationship between height and weight, you need to include a graph of weight vs. height. Remember, the independent variable (the one you manipulated directly) on the x-axis, dependent variable (the one you were watching to see how it would be affected) on the Y-axis. Additional notes about graphing.
It is appropriate (even expected) to include a line or curve of best fit. This is your way of expressing what you think the data would look like if we could make perfect measurements. DO NOT "connect the dots" here; there aren't and hidden pictures of bunnies. Note that this is something you should do AFTER you've analyzed uncertainty and added uncertainty bars to your graph (described below).
Uncertainty
Describe the sources of random uncertainty in your data. "Human error" is not sufficient here. Also, describe the amount of uncertainty associated with each measurement type.
When uncertain measurements are used in calculations, the calculated answers have uncertainty, too. Use this section to show your work determining the uncertainty in all calculated values.
Uncertainty is a very big topic. Click here for notes about how we'll approach uncertainty in this class.
It can be useful to add a visual representation of uncertainty to your graphs from the analysis section. See the additional notes about graphing for more details.
Conclusion
Effectively, this answers the question or purpose you wrote at the beginning of the lab
This should be informed by and reference your data, graph(s), and work with uncertainty.
Example: "Based on the shape of the graph of pendulum period vs. length, it appears that the period is proportional to the square root of the length. Initially, we believed that the two quantities would be proportional, but there is no straight line that can be drawn from the data collected (even including the uncertainty bars). Instead, we find a curve, and fitting a variety of curves to the data using a calculator led us to find that a square root curve fits better than any other simple relationship."
This is also the place to suggest modifications to the procedure that you weren't able to make, or outline future experiments that might provide more reliable data to answer the questions you were trying to answer.
Example: "It stands to reason that, since a cord will stretch slightly when it is tensioned, the string on this pendulum may have gotten slightly longer or shorter during its motion. This might have affected the measured period slightly, since the length was measured when the string was unstretched. To analyze this effect further, it would be interesting to deliberately choose material for the cord that is stretchy and analyze the factors that determine the period of a pendulum with a very stretchy string. For example, a larger amplitude of motion should cause a higher tension in the string at the bottom of its arc, which would make the cord get longer and might affect the period."
Lab journals also include new ideas, changes to procedures, questions that come up during experimentation, observations made during experiments, etc. If you do it, say it, hear it, or think it during a lab and it seems like it might be important later, make a record of it in your lab journal. My college lab journals are full of things like, "The data we've gotten during this run is inconsistent. For the next set, we'll try cleaning the surfaces with acetone before injecting the oil droplets." These notes are spread throughout various section in the lab journal entry.
Lab journals are not formal lab reports, so changes, revisions, additions, and "hmmm, that's interesting" statements are expected. There are plenty of anecdotes of scientists making what turn out to be big discoveries, but starting out by thinking there was just some problem with their experiment so they couldn't get the data they though they should be getting. As Isaac Asimov put it, "The most exciting phrase to hear in science, the one that heralds new discoveries, is not “Eureka” but “That's funny...”