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\centerline{MONT 105N -- Analyzing Environmental Data}
\centerline{First Writing Assignment}
\centerline{Due: no later than 5:00pm on Friday, February 28}
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\noindent
{\it Background}
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Since our class has taken on the analysis of the ``carbon footprint audit" data,
many of our assignments will be based on various stages of this, building up
to the projects we present at the EarthLab final event toward the end of the semester.
(Exactly how and when that will take place is still under development.)  This
means, as I said last fall, that we all need to be ready for a fair amount of 
{\it improvisation} as the semester progresses.  This means, for instance, that 
the assignment I called ``Paper 1'' on the original tentative course schedule will 
actually be more of a {\it technical report} on some next calculations with the
data.   This will involve some research, some work with this data, and 
then writing up the results in a standard format.  The due date has also been
moved one week later, to Friday, February 28.  Note:  The first journal 
collection is also due that day, but you should have been working steadily on
that since the start of the semester, ... 
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\noindent   
{\it How this will work}
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First, recall that we have data for 125 out of the total of roughly 160 students
in the Natural World Cluster seminars.  This is a response rate of $78\%$, which 
is actually not bad at all for an ``effectively voluntary'' survey of this kind(!)
\footnote{${}^1$}{I say
``effectively voluntary'' since even though the professors did do a fair amount
of cajoling to get students to respond, to my knowledge, there were no penalties
if they did not do so.}
Since we don't have data for $22\%$ of the people, we will need to use the data
we do have to estimate things like the total time spent showering, the total number
of meals at which meat was eaten, etc. for the whole cluster.  {\it You will need
to take this into account as you think how to answer the questions posed for 
your team.}
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For this assignment, you will work in {\it four teams} of four people each:
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\leftline{Team 1:  Christian, Matthew B., Augusta, and Margo}
\leftline{Team 2:  Jack, Tom, Kate, and Matt V.}
\leftline{Team 3:  Sean, Maggie, Robert, and Owen}
\leftline{Team 4:  Brooke, Caroline, Sinead, and Ming}
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\noindent
Each team will analyze one of the items from the first section of our
big data set:
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\item{Team 1:}  The electric devices information (row 6 of each page of the master
data spreadsheet) -- you'll first want to 
determine the overall five-number summary, mean, and SD of the number of
electric devices for the whole week.  (Recall the first-phase teams did this for 
their assigned days; you'll want to do the same sort of calculations for the whole week.)  
Then you'll need to estimate an average amount of electric energy being used per 
person per day based on how much electric energy different types of 
devices (e.g. mini-refrigerators, desk lamps, floor lamps, computers, etc.) draw
in a day.  This will take some research.  The College buys a contract with its
electric power supplier that essentially means we pay for the equivalent
amount of {\it hydroelectric power} generated by plants in Canada. These plants
effectively have {\it zero carbon emissions} that can be attributed to the direct 
generation of electricity. For the purposes of reporting, this means that the College
also has effective zero carbon emissions for the electric power we use.
One interesting question to ask is how much better this is compared to the New England
average of 1009.92 lb/Megawatt-hour carbon emissions for all sources of electric
power from sources that include coal-fired, and natural gas-fired electric power
plants.  How much electricity would be we using if we were getting 
our electric power from New England average sources?  Do this calculation for 
your estimated cluster-wide total for the week, then the per person per day figure.  
\item{Team 2:}  The information on meat eaten at meals (row 12 of each page of the
master data spreadsheet) -- you'll first want to 
determine the overall five-number summary, mean, and SD of the number of
meals with meat per day per person for the whole week.  (Recall the first-phase teams did 
this for their assigned days; you'll want to do the same sort of calculations for the whole week.) 
Next you will need to determine the carbon footprint of average servings
of various types of meat.  This will take some research, but this sort of
information is widely available in many places.  Since we don't have any information
about what types of meat people at each meal, you will need to come up with
an appropriate {\it weighted average} of these to represent the carbon footprint of
one meat meal for one student.  You will need to think about this and justify
the estimate you use.  Estimate the total carbon footprint of the meat eaten 
by all the students in the cluster for the whole week, then the footprint per
person per day.   
\item{Team 3:}  The information on lengths of showers (row 10 of each page of the 
master data spreadsheet) -- you'll first want to 
determine the overall five-number summary, mean, and SD of the
length of showers for the whole week.  (Recall the first-phase teams did this for 
their assigned days; you'll want to do the same sort of calculations for the whole week.)  
Recall the numbers on this row of the spreadsheet are the total numbers of minutes
spent showering.  You will next compute the total number of minutes spent showering
for all students across all 7 days of the week.  You will 
want to determine two types of information from this.  First, how much total water
is being used this way per person per day?  Robert learned that the type of shower
head used on his floor in the residence has a flow rate of 2.5 gallons of water
per minute.   Let's take that as a reasonable estimate for {\it all} of the shower heads.   
Next, let's try to estimate the carbon footprint of warming the water for
showers to a comfortable level.  How much energy does it take to raise a gallon
of water from $50^\circ\ F$ to a comfortable temperature of $110^\circ F$
for a hot shower?  I think that's a reasonable estimate for what most
people would use for a shower; most people don't like cold showers for
the obvious reasons, and not everyone likes extremely hot showers either!  
(For instance, a shower water temperature of $120^\circ F$ would cause skin burns 
in under $5$ minutes.)  Are the hot water heaters in the residence
electric? gas-fired?  What would be the 
carbon footprint of that energy source if we were using the New England average
electric power?  (See description for Team 1's question above!)  Do this as a total,
then per person per day.  
\item{Team 4:}  The information on single-use plastic containers (row 14 of each page
of the master data spreadsheet) -- -- you'll first want to 
determine the overall five-number summary, mean, and SD of the number of
containers for the whole week.  (Recall the first-phase teams did this for 
their assigned days; you'll want to do the same sort of calculations for the whole week.)  
Also estimate the total number of containers used by all the students in the cluster.
Next, you will need to make a reasonable estimate about the carbon footprint
of one of these containers.  I expect that almost all of these containers
that were reported were plastic water or soda bottles and that almost
all of them were 20 oz. size plastic containers (or at least the size would
average out to that).  If you think we should
consider other sizes or other types of containers too, than that is fine, but
you will need to come up with reasonable estimates for how much plastic is
contained in all of them.  Look up how much plastic is contained in a 20 oz.
water or soda bottle and what the carbon footprint is of manufacturing and
distributing them.  This will take some research, but you should be able
to find good figures in many different places.  Report your findings as a
total carbon equivalent value for the whole cluster for the whole week, and 
also as an individual figure per person per day. 
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\noindent
{\it The technical report}
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Please write up your findings as a ``technical report'' in a Google Doc. 
This should end up being roughly 4 to 5 pages.  Please try to have all team 
members contribute to the write-up.  
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{\it Important Note:}  Please {\it do not} write a narrative stating ``we did this 
and then we did that, and then ... .'' The report should give your final
results and conclusions, backing up what you say in detail.  
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\noindent 
Follow this outline, including section headings {\it exactly as here}:
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\item{1.}  {\it Introduction} -- state the question(s) you will consider (this can be 
a restatement of your team's assignment as above, but in your own words, and 
incorporating any changes or additions you decide to make along the way)
\item{2.}  {\it The Data} -- Describe how and when your data was collected
\item{3.}  {\it Assumptions and Additional Information Used} -- All of these topics will require you 
to gather some information related to the resource you are working with.  Give the sources
you consulted, justify why you think they are reliable, and clearly state any assumptions
you are making.
\item{4.}  {\it Calculations} -- Indicate all the calculations you did and
show in detail how the carbon footprint figures asked for in your team's assignment were derived.
\item{5.}  {\it Discussion} -- What conclusions do you draw from your calculations.  How
might what you did here factor into our EarthLab presentation or final event?
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