Lab conclusion

1) Conclusion format:
a. Minimum of 250 words starting after your name and lab title.
b. Conclusions must be written in 3rd person past tense
i. No 1st or 2nd person allowed
ii. No people words including the student, specific
names or yourself
c. ALL conclusions should be double spaced, 12-point font, Times
New Roman, regardless of a hard copy or digital submission.
d. Margins should be 1 inch on all four sides.
e. Header expectations:
i. First line- Left align with your name
ii. Second line- Center align with the title of the experiment
iii. Third line- Begin your conclusion
2) Your conclusion should start with a brief summary of the objectives and purpose of the lab, which should be written in the form of a thesis statement (Ex: In this lab aspirin was synthesized with a purity of 98.5%) Supporting sentences for this thesis statement should include a very brief summary of the lab (1-2 sentence procedure summary recap, no more). This opening should comprise no more than 50-75 words of the conclusion.
3) The conclusion is primarily a discussion about the DATA. You should make sure that your conclusion discusses the data collected, along with analysis of any calculated results. There should be a discussion about the data collected, including the appearance of the numerical data from the lab in your conclusion. Discussions of how the data was obtained are acceptable but focus on how the data fits together to piece your results of the lab together. Also include in your discussion of the data any circumstances that could have caused misinterpretation of the data (this will be referred to in this class as sources of error or uncertainty).
4) Be sure to define every pronoun. For instance, if you state, it was then filtered using a Buchner funnel, the reader should be able to determine from the current sentence what it is. DO NOT ASSUME that the reader knows what you mean. I recommend that you have someone not in the class read the conclusion to ensure they can follow. If they cannot follow it, you need more details in your discussion. You should highlight any new techniques used or specific equipment utilized in the particular experiment.
5) The conclusion should include appropriate usage of pertinent vocabulary. Each topic in your conclusion should be in its own paragraph. This paragraph should be followed by a paragraph describing a short summary of how you accomplished. DO NOT INCLUDE A STEPWISE PROCEDURE IN THIS SECTION!!! The next paragraph should discuss your results and potential sources of uncertainty. Uncertainty does NOT refer to human errors unless they are uncorrectable. For instance, spilling your product would significantly reduce your amount of product you isolated. It is a valid uncertainty to report in your conclusion. Reading your balance incorrectly is something you should ask for help and is NOT a source of uncertainty. (You can correct a misread mass by checking your technique and remeasuring mass). Read Mr. Lesmeisters Handout Dealing with Experimental Uncertainty below. What part of the procedure where they introduced?
6) Your sources of uncertainty must be linked to your data collection and procedure and the effect that uncertainty had on the end calculation. In other words, why was the calculated number too high or

too low? What step caused the collected data to be off in such a manner that it would make the end calculation off in the manner determined in the lab?
7) Make sure you actually summarize and discuss the data in the results paragraph, provide examples, not a rewrite of your data table. Calculations should not be presented, only the results of the calculations.
8) Grammar counts, spelling counts. Use complete sentences and logical discussions.
Dealing with Experimental Uncertainty
In science, we construct models to describe reality. We test these models by taking measurements and comparing the results of those measurements with the predictions of our models. Comparing results with predictions is not simply a matter of asking if two numbers are equal. No measurement is ever perfectly exact; all real measurements have some uncertainty. Thus, in order to compare our measurements with our predictions, we need to know how uncertain our measurements are.
There are three main sources of experimental uncertainty. Each source must be dealt with in your lab work. The first source of experimental uncertainty is the mistake. Misreading a scale on a meter, or writing down the wrong digit in a number are examples of mistakes. Mistakes should be corrected when they are discovered. If a measurement was misread or written down incorrectly, draw a line through the incorrect number and redo the measurement. If a calculation was done improperly, draw a line through the incorrect calculation and redo it. Sometimes one discovers that all the measurements on a lab were done improperly. If that is the case, and time allows, all the measurements should be redone. That is why its a good idea to know approximately what values are expected for a measurement, so you can immediately see if your values are reasonable.
The second source of experimental uncertainty is systemic errors. Although they are called systemic errors, they should not be confused with mistakes. A systemic error results from the way the measurement was taken and always affects the measurement the same way. For example, a measurement involving a string may assume the string does not stretch. However, real strings may stretch, and so the string was actually longer when it was being used than when it was measured beforehand. Systemic uncertainty results in measurements that are inaccurate, that is to say, although the measurements may agree with each other, they deviate from the real or expected value in a consistent way. Causes of systemic errors should be dealt with if possible. Those that cant be corrected should be discussed in the conclusion section of your lab report.
The third source of experimental uncertainty are called random errors. Again, although they are called errors, they are not mistakes, but are inherent variations in repeated measurements that cannot be predicted. Air currents and power supply fluctuations are examples of things that can cause random errors. Because random errors cause repeated measurements to deviate from each other, random errors result in measurements that are less precise than they otherwise would be. Sources of random error should be identified in the conclusion section of your lab report. The rule of thumb is, deal with mistakes