Bi 253 Lab Exercise 1.
Data Analysis and Reporting
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Introduction
The purpose of this lab exercise is to show the techniques for reducing and
presenting data and how to write a lab report. For most of the exercises this
term you will write a short report in the style of a research article. This will
involve finding at least one relevant article from the scientific literature and
learning how to reference it.
The first step is to collect some data, but for this introductory lab you
will have some fake raw data to work with. These will be analyzed and you
will make some figures that go into the lab report. The analysis and figure
preparation will use Excel and the text will be written in MS Word. When
you produce lab reports subsequently in the course you may use software of
your choice. There are several good freeware clones of MS Office that will
work adequately; in particular Libreoffice is a good choice that will run on
Mac OS-X, Windows (although perhaps not Windows 8) and Linux.
Some of you may have laptops or tablets in lab with you, and then you
can work somewhat independently. For those who do not there is the lab
station computer. If more than one person in your group is sharing the lab
station computer, then you will make a single lab report which you will all
use instead of an individual report. In the future, however, all parts of your
lab report, with the exception of the raw data, must be produced by you
alone.
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Reducing Data
One simple but important thing to keep in mind is unit conversion. Sometimes you will collect data that must be converted to appropriate S.I. units.
For example, you might collect weight data from your student partners in
pounds (lbs) but for scientific purposes, these values must be converted to
kilograms (kg). Sometimes there are multiple standards in use. Blood pressure in the United States medical community is only reported as millimeters
of mercury (mmHG) which is a terribly old standard not used elsewhere.
The correct S.I. unit for pressure is Pascals (Pa).
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To do the conversion you can (1) find a web calculator, (2) use any number
of smart phone apps or (3) if you have a mac or linux computer use the “units”
program that comes bundled with the operating system. Finally, if you have
a number of values to convert MS Excel is most convenient, and this is what
we will do later in this lab exercise.
For your first simple exercise, convert the following measurements to the correct S.I. units:
1. 60 lbs to kilograms
2. 40 miles per gallon to liters per kilometer
3. 87 degrees Fahrenheit to degrees centigrade
4. 140 mmHg to Pascals
The next data reduction consideration has to do with reporting numbers.
Consider a behavior experiment in which you observe pillbugs escaping a hot,
bright light source. Pillbugs like cool dark places, and so will move quickly
away from the light. Suppose you have determined that the pillbug retreats
at 2.5 cm per minute. Other students collect similar data which you pool to
get an average. You might have something like the following.
pb1
pb2
pb3
pb4
pb5
2.5
3.1
2.9
1.6
1.8
The average is, of course,
(2.5+3.1+2.9+1.6+1.8)
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= 2.38cms−1
If your TA sees this result in a lab report, there could be a bit of an
issue. How so, looks perfectly alright? Well, to make the point with a bit
of exaggeration, suppose your pillbug speed was reported as 2.38475920 cm
s−1 . Did you really measure the speed that accurately? How certain are you
that the speed was not 2.38475921 cm s−1 ? Here are some key terms relative
to measurement:
• Resolution refers to how well you can read your instrument. If you
have a ruler divided into 1 mm tics, then you can resolve distance to 1
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mm, or arguably to 0.5mm if you see that a point is half way between
two tics. If you are reading a digital meter, then the resolution is the
number of decimal places you get. A digital thermometer might report
26.5◦ C which means that it has 0.1◦ C, or 1/10th of a degree resolution.
• Precision has to do with repeatability and essentially the quality of the
instrument you are using. Suppose you use a caliper to measure the
length of your pillbug; see Figure 1. If the caliper is a cheap plastic
tool with lots of slop in the mechanism, then each time you make a
measurement you may get a different reading. You will be able to
resolve the scale similarly each time, say to 0.1 mm, but there may not
be much consistency. On the other hand, if you purchase a $300.00
caliper that is a precision instrument, then each time you use it the
readings will be the same (when measuring the same object).
• Accuracy. Even if you have a precision instrument that has high resolution, you still don’t know if it is correct. For critical measurements
many lab instruments have to be themselves measured and calibrated
by a “standards laboratory”. In such a laboratory are kept, for example, objects of an exact known length. OK, so how do they know their
objects are exactly right? Well, ultimately all measurements in the
U.S. are related back to the National Institute for Standards and Technology (NIST). Very often you may find an instrument with a sticker
on it that will say “NIST traceable” or “NIST certified” with a date.
The certification only lasts for some time, then you have to recheck
your instrument.
If you used a ruler of unknown accuracy and low precision to measure your
pillbug distance, and perhaps using a similar quality instrument to give you
time, then how should you report your velocity? Maybe 2.4 cm s−1 is more
appropriate than 2.38, because you really can’t know the real value to 0.01
cm s−1 . Very often the trouble begins when you scale values by multiplication
or division, because your calculator will report many decimal places – it is
just doing math and does not know about your science experiment! By the
way, one of the worst offenders for lab instruments are temperature meters.
They often will give you a readout to 1/100th of a degree, but if you look up
data on the sensor used in the device, often it is only “good” to 0.5◦ C. Said
another way, the resolution is inappropriate for the precision.
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Figure 1: Measuring your pillbug
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Data Reduction and Analysis with Excel
R
In this section you will work with some data as it might be collected during
a real experiment. Also, your TA may have you fill in some of your own data
in a table – see the very end of this exercise. In Table 1 are some values for
human weight, height and and age.
Some fake student data
weight (lbs) height (inches) age (yrs)
250
69
25
185
75
31
175
68
43
200
71
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Table 1: Data from some students who might be in your lab
group
Many, or perhaps most of you may be familiar with Excel, but it is
important that everyone have a handle on how to use Excel for reducing
and plotting data. So if you are an expert and someone in your group is
less knowledgeable, please give them a hand. The following exercise may be
pretty lame if you know your way around the program.
First we will enter into the spreadsheet the data from table 1:
Enter the data into the cells as shown. If an entry is not fitting entirely
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within a cell, go to the “Format” dropdown menu and choose “AutoFit Column Width”. Your screen should look like Figure 2
Figure 2: Entering data into Excel
Now that we have entered in the data, we want to do a calculation; in this
case we will calculate the basal metabolic rate (BMR) for our hypothetical
individuals. The formula for BMR is different for males and females, so for
simplicity we will assume that the data values are for males. The BMR
formula takes in S.I. units (kg, cm, years), however we have data in the form
of: (lbs, inches, years), so we will have to convert the units to what we need.
We could do each one by hand as in the exercise above, but the whole point
of spreadsheet programs like Excel is to do multiple calculations like this for
us. First, lets make a new column for the converted weight numbers. This
column should go between the current weight column and the height column.
To do this:
• Highlight the current height column (one way to do this is to click on
the top cell, hold shift and then click on the bottom cell).
• Right click on one of the highlighted cells.
• Choose the “insert option”
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• From the popup menu, choose the “Shift Cells Right” option.
• Click “OK”.
Now your screen should look like Figure 3.
Figure 3: Set up for a simple calculation
In the top cell of this new column, type something like “Mass(kg)”. Now
we need to convert lbs. to kg. Looking at your set of conversion factors, it
looks like 1 pound = 0.454kg. Thus, we will have to multiply each persons
weight in pounds by 0.454 to get their weight in kg. Figure 4
• Select the first cell under “Mass(kg)” by clicking on it.
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• Type “=B3*0.454”. Notice that everything you type after “=” comes
up in the equation box above the cells.
• Hit enter.
Figure 4: One converted mass value
You should now have the weight of the first person in kg. in that cell, as
per Figure 4. To do the rest of the column, you dont have to type in an
equation for each number, since its simply the same equation with sequential
cell numbers. We just need to copy the formula in the row where you entered
it into other rows, i.e., do a “row copy”. Here are the steps, and the result
is shown in Figure 5
• Right click the cell we just calculated.
• Choose the “Copy” option.
• Now select the entire column, just as before.
• Right click on one of the selected cells.
• Choose the “Paste” option.
You should now have an entire column of weights in kg.
Now, repeat these steps with the appropriate changes (naming columns,
conversion factors) to convert the “Height” column from inches to cm.
The next thing we will do is perform a calculation. By reviewing the
scientific literature (there will be more to say about that shortly) we learn
that you can determine the basal metabolic rate (BMR) from height, weight
and age values. How to do this is given by the following equation:
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Figure 5: The formula will be applied to all four rows
Pmen =
13.75m 5.0h
6.76a
Kcal
+
−
+ 66.47
1kg
1cm 1year
day
and
Pwomen =
9.56m 1.85h
4.68a
Kcal
+
−
+ 655.10
1kg
1cm
1year
day
Where m = mass (kg), h = height (cm), and a = age (years).
The spreadsheet entry for the equation looks like this (Figure 6) which
is entered with these steps:
• Select the first cell in the BMR column by left clicking on it.
• Type (without quotes) into the cell this equation: “=13.75*C3+5*E36.76*F3+66.47”.
• Hit enter.
• You should now have the BMR for that person in the first cell of that
column.
• To do the rest of the males in that column, copy the cell we just calculated, select the rest of the cells in that column (as before), right click
and choose paste.
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Figure 6: Entering the BMR equation
You should now have BMR data for the entire male column of data. Its
a good practice to glance over the final data output and make sure it makes
sense. Typically, BMR output from this equation will be from 1000-2500
kcals a day. Use your own judgement to decide if the output looks wrong
(obviously, if youre getting 6 million kcals a day as your output, something
went wrong, but if its saying 700 kcals, its possible that you just have a very
small person of a certain age).
Now we will expand our data set by collecting data from each other (but
only with your permission!). Of course we don’t have BMR values, but
certainly we can get height, weight, age and gender. There are some meter
sticks taped to the wall for obtaining height, and you probably know your
weight. If not, perhaps your driver’s license is a good place to check... or you
can just guess. Make a tables with column headings for height, for age, and
for weight. There should be one table for males and one for females. Once
you have your data, use Excel to determine these results:
• From the female data re-run the calculations for BMR, as you did above
for the fake male data. You can also do your new male data.
• Calculate some simple statistics: the mean and standard deviation. The
calculations should be separate for the male and female data.
Your TA will help you find the mean and standard deviation
with Excel. Standard deviation is a measure of how much variability you
have in your data. It is a common question in biology to ask if two populations are different. For example, are voles from California larger than
voles from Oregon. Suppose you go out to the field and get a lot of weights
from California voles and a lot of weights of Oregon voles by spending the
summer trapping the little buggers. Then you calculate the mean weight for
each population of values. Say you find Calvoles have a mean weight of 22
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grams and Orvoles are 23 grams. Are they different? Well, 22 is not 23 so
they must be. Hmm, not so fast! Suppose the variation in weight is so great
that half of the heavier Calvoles weigh more than half of the lighter Orvoles.
You would not be very confident in saying that they are really different. A
simple statistical test would tell you exactly how confident, and this test
is based on the standard deviation of each set of weight values. Although
unlikely, it is possible that the Calvole values come in like 21.5, 22.1, 22.0,
21.9 and so forth, while the Orvole values look like 22.9, 23.1, 23.5, 23.0. In
other words, you never see Calvoles as heavy as Orvoles. Now the variation
is much less, and the standard deviation measure would therefore also be
less, and you might be pretty safe in saying the populations of voles do not
weigh the same. Graphically, the way you illustrate the amount of variation
with a bar plot is to add a bar to the bar! You put an error bar at the top of
the bar showing the mean value. The length of the error bar is equal to the
standard deviation. If two bars you are comparing are different in height,
because the mean values are different, then by looking at the error bars on
them you can get an idea if the mean difference really says something. If
the error bars do not overlap each other, there is a very good chance that
statistically the means are really different.
By the way, if you perform a statistical test to show that two populations
have different means (or some other statistical test), then you can make a
statement like “population A is significantly different from population B”.
Unfortunately, it is common when writing to use the word significantly to
emphasize that there is a large or prominent or obvious difference, but when
making a scientific report you cannot use the word significantly unless you
have actually done a statistical test. It is a reserved word!
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Data Presentation
R
Graphs for scientific presentation are more precise than the standard Excel
spreadsheet graph. Axes markings and labels must be done correctly, and
the data properly presented. Much of this is “style” and one could argue
that style does not matter if the results are there, but this is not the case.
If the reader has to puzzle over your data plot it is probably due to poor
presentation. In this class we would like you to develop a sense of pride in
presenting your results, and that means making figures with care.
One important convention for x-y or scatterplots is to put the dependent
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variable on the Y (vertical) axis and the independent variable on the X (horizontal) axis. The independent variable is the one the controls the dependent
variable. For example, later you will make a plot of weight vs. age. We
know that as people get older then tend to put on extra pounds, so weight
depends on age, but not the other way around. Thus such a plot would have
the variable age on the X axis and the variable weight on the Y axis.
Here are some graph presentation techniques to keep in mind:
• Axes should have tic marks, and the last tic mark should be at the
end of the axis. That is, there should not be a long portion of axis
extending beyond the last tic.
• The labels for the tics should be large numbers, not the microscopic
ones often produced by default.
• Tics should be at reasonable intervals. For example, tics at 3.45 4.27
5.19 should be replaced with tics at 3 4 5 or perhaps 1 5 10, depending
on the axis range.
• Axes should be labeled descriptively, and indicating the units. For
example, “Blood Pressure (mm Hg) ”, or better yet “Blood Pressure
(Pa) ”
Bar charts can have spaces between the bars that are adjusted on the
basis of style and labeling, but for histograms, there are some fine points for
best results:
• The histogram bars should not have random spaces between them, as
is common with bar graphs or bar charts.
• Ideally, the each bar should be at the midpoint for the interval, with
the bar width exactly the interval span. Like this: Suppose you have
histogram intervals of 4 units. So bin 1 is 0 to 3.99, bin 2 is 4.00 to
7.99, bin 3 is 8.00 to 11.99 and so forth. The center of histogram bar
1 would be at 2.00 and the width of the bar such that it extends left
down to zero and right to 3.99.
You should not put the same data in a table and in a graph. Pick the
best format and just show your data once. Tables should include headings
and units for the values.
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The following instructions take you through the process of making a scatter plot, which is data shown in two dimensions, x and y. What data will we
use? Now that you have calculated some BMR data, you might be wondering
what physiological factors influence BMR. According to recent research [1],
the best known predictor of BMR is fat-free mass (the mass of your body
minus any fat). Suppose that you wanted to see if this research is right. You
go out and grab 15 random people, measure their fat-free mass (never mind
how), then you measure their BMR. You now want to find out if there is any
correlation between the two variables.
Starting in Excel, enter your data into two columns (the first one labeled
as Fat-Free Mass (or FFM) and the second one labeled BMR as shown in
figure 7.
Figure 7: Entering mass and BMR data.
Now, highlight both sets of numbers, go to the “insert” tab, then choose
“Scatter”. This is shown in figure 8 and gives the result shown in figure 9.
If you wanted to change the style of any part of the graph, right click
on that part of the graph and choose the “Format” option. For example,
if you wanted to change the style of the data points, right click on one of
them and choose the “Format Data Series” option. If you feel that the range
displayed is not optimal, right click on the axis that you feel is wrong and
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Figure 8: Select the scatter plot graph option.
choose “Format Axis.” From the “scale” tab, you can manually enter in
maximum and minimum values for that axis.
Figure 9: The initial data plot.
Now you will want to add labels to your axes, as well as a title for your
graph. The easiest way to do this is to go to the “Layouts” tab under “Chart
tools” and choose the first option. You should now have a graph with a title
and axes labels, all you have to do is click on the individual labels and/or
titles and type your own labels.
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Scientific graphs nearly always have tic marks on the axes, and Figures
10 and 11 show you how this should go.
Figure 10: First step in tweaking the axes.
The next thing we will do is add a trendline to the scatterplot. This is
often done to give a good visual representation of the slope of the data values.
When there is a lot of variation in the data, a non-zero slope may be hard to
appreciate. The trend line is calculated using a statistical technique called
linear least-squares regression and often the trend line is called a regression
line. How the calculation works is a bit more than we want to get into for
this lab, but Excel makes it easy to get the result. See Figure 12 for how
to do this with your data. Your final graph should now look something like
Figure 13. Note the comment on the figure that R2 = 0.9152. What does
this mean? When you calculate a regression line you would like to know the
extent to which your population of points actually follow the line. That is to
say, you want to know if there is a correlation between the independent and
dependent variables. If you had a random cloud of points, then just about
any X value could have an associated Y value over the whole range of Y
values. On the other hand, if there is a strong correlation, as the X values go
up (or down) the Y values follow systematically. So a large X value can only
have a large Y value associated with it. The regression calculation offers up
this result: The correlation coefficient, sometimes just called the “R value”.
An R value can range from 0.0 (no correlation at all) to 1.0 which is a perfect
correlation. Well, actually it goes to -1 too, for the case where one variable
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Figure 11: Second axes adjustment.
goes down predictably as the other goes up. Now the “R2 value” is related:
Not surprisingly it is the R value squared, and gives the “goodness of fit”
between the trend line and the data points. For our data the R value is
about 0.96, which is very good. That is to say the data are highly correlated.
When this is the case you would expect the trend line to fit well, and thus we
see the correspondingly high R value. Finally, it is important to note that
correlation is not the same thing as causation. Dont forget that your graphs
should always have units on them, as well as a descriptive title.
Figure 12: Adding a trend line to your scatter plot.
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Figure 13: The final plot
So we have made a proper scatterplot, how about a bar chart? Recall you
have two populations of height, weight and age data values, one for males
and one for females. You used Excel to determine the mean and standard
deviation. Now try to produce a bar chart with one bar representing
mean height for males and another bar representing mean height
of females. The height bars should include standard error bars. You can do
the same for weight. This figure can be figure 1 in your lab report due next
week. Your TA will help you with this if you are not arriving at a satisfactory
result.
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5
Organizing your lab report
Now you should have your data reduced and figures prepared. You know
what results you have obtained. The next step is to start building your lab
report. A scientific report is organized this way:
• Introduction. Here you give background information. For example,
with the metabolic rate lab you might talk about how much food animals consume, a range of oxygen consumption for different kinds of
animals, the effect of age or exercise or whatever on metabolic rate.
You could talk about different methods for measuring metabolic rate.
• Methods. Now you describe how you went about collecting your data.
• Results. In the results section you present your data descriptively, and
with tables and figures. Each table or figure must be numbered, in the
order presented. Usually the same data is not shown in both a table
and a figure.
• Discussion. Now you talk about what you found in the context of what
others have found. You might think this is just like the introduction,
but there is an important difference. In the introduction you might
make a statement like “Humans have a relatively high basal metabolic
rate, compared with other mammals (Poindexter 1932)”. This is introducing the reader to what is known about human metabolism. When
you are writing the discussion, you would make a statement more
like this: “Due to our leaky apparatus it was not possible to see a
clearly defined BMR, as has been shown using the Hossenpfeffer method
(Poindexter 1932). In other words, you compare your results with expectation. You don’t have to explicitly reiterate every citation from
the introduction.
• References. These are the sources of information that you discuss in
relation to the experiment performed and the data you obtained.
For the next part to the exercise you should open MS Word and
make a “skeleton” for your lab report. Make headings for each of
the sections of the report (Introduction, Methods, etc).
So you have your headings, but what do you say? How do you introduce
the experiment? It is best to know what is going on, yes? How about we
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know find a scientific article or two that relate to the experiment. Since we
got data on basal metabolic rate in humans, this is what we should hunt
for. Parenthetically, you should realized that in a research lab the literature
search is the first step. You would never undertake an experiment without
knowing what else has already been done.
The PSU library has several very comprehensive scientific databases you
can use. Biosis and Medline are two. In many cases, to get access to the full
text versions of articles found with databases you must do your search from
a university computer. The reason for this is that PSU pays for access to
the journal contents. It is very expensive! In most cases, Google Scholar is
a perfectly adequate as a way to find articles, albeit with a bias to the more
recent ones. Doing a Google Scholar search for “basal metabolism human”
yielded the results shown in Figure 14.
Figure 14: Looking for relevant articles.
Note the links to the right of the article citations where you can get the
actual article. Sometimes you will see “find it at PSU” which means the PSU
library has a copy or electronic access to one. If you do the same search from
your home or laptop computer then the links may not appear, or when you
click on them you will be directed to the publisher’s web site. Sometimes
the articles are free, but often the publisher will want you to pay a large fee,
perhaps $35.00 for an article. There is no need to do this! Just use a PSU
computer. As a last recourse you can request an article through Interlibrary
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Loan (ILL) and there is a link on the PSU library web site for this. It can
take a few days, though.
So the last article on the list looks interesting. When you click on the
link you get the front page of the article and lots of ancillary information. A
little hunting reveals a link under the heading “Access” to “Full Text (PDF)”
which is what you want. Soon you will have the exact article in your hands.
The first page of the article looks like Figure 15. Well, we will have to read
the article and get information related to the metabolic data you “obtained”
in lab.
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Scientific Referencing
When you write your lab reports you should adhere to the standards for
scientific article referencing. The first thing to keep in mind is that a reference
list, which you will provide in your report, is different from a bibliography.
In a bibliography you may include many relevant works even if they are not
explicitly referenced in the text of your article or report. When you write
a scientific article or lab report, every point that must be backed up should
have a reference associated with it, and every item in your reference list must
be referred to from the text.
What points need to be backed up? This is a bit of an art and there are
no strict rules. For statements that everyone would immediately accept as
true and obvious there needs to be no reference. For example, if you had a
statement in your report that “Humans maintain a basal metabolic rate” no
reference would be needed. It is unlikely anyone would object to this idea.
On the other hand, if you made this statement: “Based on the insulating
properties of skin and subcutaneous fat, humans can tolerate temperatures
as low as 22 ◦ C without seeking shelter.” then you would need to back up
the claim. The reader might want to know who, in fact, says so!
The in-text referencing style varies somewhat, but the two most common
methods look like the following examples. Here is the sentence, above, as you
might have in your report now properly referenced: “Based on the insulating
properties skin and subcutaneous fat, humans can tolerate temperatures as
low as 22 ◦ C without seeking shelter (Warm & Fuzzy, 1976)”. If there are
three or more authors, the convention is to list just the first author. Suppose
the authors are John Warm, Evelyn Fuzzy and Norman Sneezing. Now your
sentence would look like this: “Based on the insulating properties skin and
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subcutaneous fat, humans can tolerate temperatures as low as 22 ◦ C without
seeking shelter (Warm et al 1976)”. An alternative is to use numerical referencing. In this case each of the citations in your reference list has a number,
and you use that in the text. Now the sentence would appear like this: Based
on the insulating properties skin and subcutaneous fat, humans can tolerate
temperatures as low as 22 ◦ C without seeking shelter5 . The number corresponds to the entry in your reference list. If the text reference is 5, then the
Warm et al citation would be number 5 in your reference list.
Lets look at the first article we liked from the search, the fourth one on
the search page about basal metabolism and body size (Figure 15). Scanning
the front page we can glean all the bits we need for our citation:
• Authors are Craig White and Roger Seymour.
• The journal is PNAS (proceedings of the National Academy of Sciences).
• The article was published in volume 100, issue 7 and is on pages 4046
to 4049.
• The title is “Mammalian basal metabolic rate is proportional to body
mass 2/3 ”.
Here is another article found by scrolling down further on the list of hits:
An old classic review paper. Like, really old, but just the thing to reference
basic stuff about metabolism. Figure 16 shows what it looks like. As a
next exercise, extract the appropriate information from the article
page and enter this and the previous citation into the reference
section of your lab report document
If you now look at the references at the end of this document, you will
see how the reference list is properly formatted. Your task for the lab
report now is to find more relevant articles, and add them to your
list with correct formatting.
With the remaining time in lab, you should actually write up a lab report!
You can read the articles you find and start to talk about them. Of course,
scientific research articles are not easy to read and you are not an expert in the
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field of human metabolism. On the other hand, a good deal of information
can be gleaned from the introduction and discussion and without getting
bogged down in the details of the methodology. To move on to the next step,
you should export your MS Excel figures and tables and incorporate them
into the MS Word document. At this point you will at least have a report
with the correct sections, a figure and a table, and a few citations in your
reference list. A decent start!
Are you at a complete loss to find material to put in the discussion? How
about doing a Google search for BMR? If you do this many hits will come up.
One of the first things you will notice is that there is a similar concept called
“RMR”. Hmm, maybe I could talk about the difference and why there are
two similar quantities measured. Start reading one or more of the reference
articles or your text book to get more bits to discuss.
References
[1] Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO.
(1990) A new predictive equation for resting energy expenditure in
healthy individuals. Am J Clin Nutr 51( 2): 241-247
[2] Kleiber, M. (1947) Body size and metabolic rate. Physiol. Rev. 27:511-541
[3] White, C. R. and Seymour, R. S. (2003) Mammalian basal metabolic rate
is proportional to body mass 2/3 . PNAS 100:4046-4049
If you do everything you learned in this first lab exercise, will that guarantee a perfect score on all subsequent reports? The lesson above show the
minimal steps to prepare a lab report but it is the quality of your report that
will give you points above a low score.
Here are the factors that go into grading a lab report:
• Overall you will get credit for the clarity of your presentation. If the
TA has to struggle to understand what you are trying to say, or if you
thoughts are not well organized then it will be difficult to get full credit.
• The proper reduction of data is very important. Was it best to get
mean data? Is a plot or a table or a bar graph the most appropriate
to present your results?
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• The quality of graphs and tables is very important. Axes should be
properly labeled, numbers well organized so that it is easy to read.
Should your graph have just symbols? Symbols and lines through the
points?
• You should have at least one and preferably more references from the
scientific literature. You will lose points if not.
• In your discussion do you point out what is different about your data
compared to what you would expect? For example, if you get blood
pressure readings from fellow students, do they match literature values?
If not, why not?
• Are your references organized and presented properly? Points will disappear if not.
• Did you bring a bribe for your TA last week? (Just kidding - don’t do
this!!)
The teaching assistants in this course will endeavor to have a very consistent approach to grading. That is not to say that it will be perfect, but
they will do their best. First, do be aware that attendance in the lab is
mandatory. This is rule number one. If you don’t show up, but get the data
from another student and then write a wonderful lab report, it will still not
count. Furthermore, you must write up your data by yourself. If your TA
determines that you have swiped a report from another student (even if you
and the other student agree to it) and perhaps made a few tweaks here and
there so it appears to be non-identical, the report will be given a zero and
you may find yourself explaining to the appropriate academic dean why you
should be allowed to continue at the university. Academic dishonesty is a
big deal.
7
Collecting Your Own Data
Your TA will have you collect your own data to practice doing an analysis.
Below is a table for this purpose. There are meter sticks in the lab for
obtaining height. Once you have filled out the tables, you should be able
to use Excel to calculate the mean and standard deviation for male/female
height. A bar chart of these data could be figure 1 of your report.
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Men
height (cm) age (yrs)
weight (lbs)
Table 2: Data from your lab group
Women
height (cm) age (yrs)
weight (lbs)
Table 3: Data from your lab group
8
Questions to answer in your lab report
1. Use the class data to run a t-test on some of our class data. An example
of a null hypothesis could be There is no difference between the height
of males and females in our lab. Then calculate the mean, standard
deviation, and variance of whichever aspect you chose. We want to
know if these two groups are significantly different. This should be
a two-tailed t-test and we will assume equal variance. What is the
p-value? How do you interpret this result? For example, does the pvalue support the null hypothesis? (This is made easier by reading the
supplementary paper Basic Statistical Analyses.)
2. What section of your lab report would you write your p-value? What
about your interpretation?
3. Within a lab report what kind of information needs to be backed up
with a citation?
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9
Grading of your lab report
If you do everything you learned in this first lab exercise, will that guarantee
a perfect score on all subsequent reports? The lesson above show the minimal
steps to prepare a lab report but it is the quality of your report that will give
you points above a low score.
Here are the factors that go into grading a lab report:
• Overall you will get credit for the clarity of your presentation. If the
TA has to struggle to understand what you are trying to say, or if you
thoughts are not well organized then it will be difficult to get full credit.
• The proper reduction of data is very important. Was it best to get
mean data? Is a plot or a table or a bar graph the most appropriate
to present your results?
• The quality of graphs and tables is very important. Axes should be
properly labeled, numbers well organized so that it is easy to read.
Should your graph have just symbols? Symbols and lines through the
points?
• You should have at least one and preferably more references from the
scientific literature. You will lose points if not.
• In your discussion do you point out what is different about your data
compared to what you would expect? For example, if you get blood
pressure readings from fellow students, do they match literature values?
If not, why not?
• Are your references organized and presented properly? Points will disappear if not.
• Did you bring a bribe for your TA last week? (Just kidding - don’t do
this!!)
24
Figure 15: A reference25
from a first web search.
Figure 16: A snapshot of part of the front page of a really old classic article.
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