Hamburger Lab Report Instructions
General Information about Lab Reports
Authorship
Even if you worked together on the experiment, and even if you worked
together on the report, each person must turn in their own, unique report,
written in your own words.
DO NOT: pass in a report that looks substantially like someone else's.
DO NOT: pass in a report that uses sentences from your handout.
DO NOT: pass in a report that contains text lifted from a textbook or the
internet.
Working with Data
As 21st century college students, you need to know how to use computer
spreadsheet software to do assignments. This is not a software course, so you're not expected to learn Excel entirely on
your own. HELP USING EXCEL IS FREE!!! PLEASE ASK ABOUT ANYTHING YOU'RE HAVING
TROUBLE WITH, AND I WILL GIVE YOU ADVICE. Do not wait to get help. I will answer
any question I possibly can, whether by phone, email, or in person.
The data is available at this link:
Hamburger-Excel and
is copied at the end of this page. If this version of this software is not
working for you, let me know.
General Tip
One way to think about a lab report is that it is like an essay question with
data. As you write, you need to include enough so I can tell that you know what
you're talking about. Also, the report revolves around your data. Be sure to
show me that you understand how your data tell you about what has happened in
the experiment and whether the data show that you got the expected outcome.
Format
Your report should have the four sections listed below. I don't care whether
you call the 2nd section "Methods" or "Procedure", either is fine; same for the
last section. Below, each section describes what should be included, and some of
it is listed in the form of questions. I don't
want to see the questions repeated in the lab report, I just want you to weave
the answers to the questions into what you write.
Introduction:
1. Briefly described how the hamburger was treated (by me) during the first part
of the experiment.
2. In this experiment, what was it that you were measuring (that is, you as a
class)?
3. What result did you expect to see? Be specific.
4. This experiment is all about bacterial growth. Comment on the conditions that the bacteria in the hamburger were in
and how those conditions influence what you expected to see.
All of this information should be apparent to you, told to you at the start of
the experiment, and explained in the online handout.
Methods/Procedure:
1. Summarize (please!) what you did with the hamburger sample to obtain your
data.
Results:
1. You will need to calculate the dilutions and use those to determine the
actual number of bacteria per gram in each hamburger sample that was studied. If
you wish, you may include a table that summarizes your calculations. These
calculations are just like those you did for #15 in the Dilution Problem
handout. Don't forget the original dilution you made in the blender.
2. Are you allowed to use all the data in your calculations? Which values need
to be left out and why? Consult your handout and these instructions.
3. The key part of your Results section is the graph that shows how the number
of bacteria in the hamburger is changing with time. Be sure you convert your
numbers as necessary so you can demonstrate with your graph whether the bacteria
are doubling at regular intervals or not. Be careful that your graph has
all the necessary labels (and no unnecessary ones) and that your X axis is
linear (use the "xy scatter" menu choice in Excel). Do NOT average any data! Use
all eligible data points in your graph. I will be happy to explain why if you're
interested.
Discussion/Conclusions:
1. Do your data allow you to conclude what you predicted in your Introduction?
How does your graph support your conclusion?
2. Although we usually think about generation time with respect to a pure
culture, the mixed community of different bacteria also, as a group, has a
generation time. Calculate the generation time of the bacteria in the hamburger.
Use what you learned from Growth Problem #2 from your Dilution problems/Growth
problems handout. This calculation is made much easier by obtaining the equation
for your trendline using Excel.
This report will be due by Friday, October 10.
Special Notes about using your data:
For the first time ever, this experiment was a bust!
The data that you have been given are from 2003. At that time, the afternoon
class met starting at 3:00, not 2:00, so the time calculations will be different
(see below).
When using viable plate counts, the usual requirement is that the number of
colonies be between 20-200. We are sticking to that rule. Don't forget to calculate the time spent at room temperature for each hamburger
sample. Double check your work, because your
graphs and conclusions will be messed up if the correct times haven't been
calculated. The rest of the calculations may take a while, although with Excel I
did it very quickly. Each (usable)
value must be multiplied by the correct dilution factor. You may directly graph bacteria
(CFU) vs time, but it will be more important to make additional data conversions to make a useful graph (resembling Growth Problem #2).
For this graph you should create a trendline. This is needed to calculate generation time.
I have included ALL the data.
Class= | am | Class= | am | Class= | am | Class= | am | |||
Sample= | Sun 3:30 p | Sample= | Sun 9:30p | Sample= | Mon 6:30a | Sample= | Mon 9:30a | |||
Plate: | colony ct | Plate: | colony ct | Plate: | colony ct | Plate: | colony ct | |||
a1 1.0 ml | ND | a1 1.0 ml | ND | a1 1.0 ml | TNTC | a1 1.0 ml | TNTC | |||
a2 1.0 ml | ND | a2 1.0 ml | ND | a2 1.0 ml | TNTC | a2 1.0 ml | TNTC | |||
a1 0.1 ml | ND | a1 0.1 ml | ND | a1 0.1 ml | TNTC | a1 0.1 ml | TNTC | |||
a2 0.1 ml | ND | a2 0.1 ml | ND | a2 0.1 ml | TNTC | a2 0.1 ml | TNTC | |||
b1 1.0 ml | TNTC | b1 1.0 ml | TNTC | b1 1.0 ml | TNTC | b1 1.0 ml | TNTC | |||
b2 1.0 ml | TNTC | b2 1.0 ml | TNTC | b2 1.0 ml | TNTC | b2 1.0 ml | TNTC | |||
b1 0.1 ml | TNTC | b1 0.1 ml | 205 | b1 0.1 ml | 92 | b1 0.1 ml | 179 | |||
b2 0.1 ml | TNTC | b2 0.1 ml | TNTC | b2 0.1 ml | 55 | b2 0.1 ml | 36 | |||
c1 1.0 ml | 229 | c1 1.0 ml | 196 | c1 1.0 ml | ND | c1 1.0 ml | ND | |||
c2 1.0 ml | 167 | c2 1.0 ml | 60 | c2 1.0 ml | ND | c2 1.0 ml | ND | |||
c1 0.1 ml | 37 | c1 0.1 ml | 17 | c1 0.1 ml | ND | c1 0.1 ml | ND | |||
c2 0.1 ml | 23 | c2 0.1 ml | 15 | c2 0.1 ml | ND | c2 0.1 ml | ND | |||
Class= | pm | Class= | pm | Class= | pm | Class= | pm | |||
Sample= | Sun 3:30 p | Sample= | Mon 6:30a | Sample= | Mon 9:30a | Sample= | Mon 3:30 p | |||
Plate: | colony ct | Plate: | colony ct | Plate: | colony ct | Plate: | colony ct | |||
a1 1.0 ml | ND | a1 1.0 ml | ND | a1 1.0 ml | TNTC | a1 1.0 ml | TNTC | |||
a2 1.0 ml | ND | a2 1.0 ml | ND | a2 1.0 ml | TNTC | a2 1.0 ml | TNTC | |||
a1 0.1 ml | ND | a1 0.1 ml | ND | a1 0.1 ml | TNTC | a1 0.1 ml | TNTC | |||
a2 0.1 ml | ND | a2 0.1 ml | ND | a2 0.1 ml | TNTC | a2 0.1 ml | TNTC | |||
b1 1.0 ml | TNTC | b1 1.0 ml | TNTC | b1 1.0 ml | TNTC | b1 1.0 ml | TNTC | |||
b2 1.0 ml | TNTC | b2 1.0 ml | TNTC | b2 1.0 ml | TNTC | b2 1.0 ml | 198 | |||
b1 0.1 ml | TNTC | b1 0.1 ml | TNTC | b1 0.1 ml | 299 | b1 0.1 ml | 401 | |||
b2 0.1 ml | TNTC | b2 0.1 ml | 222 | b2 0.1 ml | 199 | b2 0.1 ml | TNTC | |||
c1 1.0 ml | TNTC | c1 1.0 ml | 38 | c1 1.0 ml | ND | c1 1.0 ml | ND | |||
c2 1.0 ml | 371 | c2 1.0 ml | 45 | c2 1.0 ml | ND | c2 1.0 ml | ND | |||
c1 0.1 ml | TNTC | c1 0.1 ml | 4 | c1 0.1 ml | ND | c1 0.1 ml | ND | |||
c2 0.1 ml | 88 | c2 0.1 ml | 11 | c2 0.1 ml | ND | c2 0.1 ml | ND |
Class: am or pm. Columns headed with "am" were data obtained a 9:30 Monday morning. Columns headed with "pm" were obtained at 3:30 (not 2:30!!) Monday afternoon. "a" is the first dilution, "b" the second, etc. a1 and a2 are duplicates of each other. TNTC means too numerous to count. ND = not determined. The data are NOT in any particular order other than from least to most dilute.