In this
lesson you answer a research question using WOW data. Your final presentation
is a scientific poster. The "Reporting Results" section provides
specific instructions for formatting the final presentation.
Knowledge
Base
Many student
experiments are designed to demonstrate a particular principle discussed
in lecture. All of the exercises should work since they have been tested
prior to your arrival in the laboratory. This isn't how scientific research
is performed.
Consider how
scientific research might differ from laboratory exercises.
Researchers
begin with observations and questions that lead them to a hypothesis.
An experiment is then performed, and the results confirm the hypothesis
or provide reason for change. Sometimes experimental results point the
researcher in a completely new direction.
Experimental
results and the researcher's interpretation of them are crucial to the
development of new ideas, hypotheses, explanations, and theories. A researcher's
ability to interpret data can be both a learned skill and a gift. Although
some individuals are better at data interpretation than others, practice
sharpens observation and interpretive skills and leads to a more complete
analysis of the data.
Be certain
to review data as you prepare to answer your question. Think about relationships
among data and relationships among data and the external factors. Also
consider your reflection as you form a hypothesis.
Initially,
focus on no more than two variables. Record your thoughts, impressions,
and ideas on paper. Review these periodically. Think about relationships
among data. Think about relationships among the data and other external
environmental factors, such as rain, wind, sunlight, etc. Use your reflections
to form a hypothesis.
Experimental
Design
Your teacher
will assign a research question.
Possible Research
Questions:
- What water
depth is most affected by sunlight? Why?
- How does
thermal stratification change throughout the summer months? Why?
- At what
depth does biological activity seem to be most significant? Why?
- Which lake
exhibits greater biological activity? Why?
- During
what time of the year is biological activity at a maximum? Why?
- Are daily
pH and dissolved oxygen levels related to one another? Why?
- Where in
the lake are the largest daily pH swings observed? Why?
- What depth
exhibits the greatest daily changes in dissolved oxygen? Why?
- Is there
a relationship between daily water temperatures and dissolved oxygen levels?
Why?
- How does
dissolved oxygen depend on depth? Why?
- How does
lake water temperature depend on depth? Why?
- Can the
effects of storm activity be identified within the RUSS data? How?
- Is there
a relationship between conductivity and pH? Explain.
- Are there
seasonal patterns in turbidity? Explain.
- Does the
relationship between a lake's acreage and its watershed's acreage
affect turbidity? Explain.
- Is there
a relationship between cooling days (or degree days) and the onset of
stratification in a lake?
Data Collection
Access the
WOW site and download the required data in Excel format.
Other resources
available include class notes, handouts, books in the library, and the
Internet. Additional resources are available on the WOW site. Clearly
reference any resources used in the data analysis on the poster.
Data Management
and Analysis
Use the RUSS
data to answer your research question. Be sure to title your graphs and
labels axes and legends.
Remember that
all experimental data consist of measurements that have one, rightmost
uncertain digit. Although the RUSS unit is a sophisticated robot, it
is still only a measurement tool. Be sure to consider how much you believe
each of the digits in any measurement.
Sometimes,
data are found that defy the observed pattern. These are known as data
outliers. Rather than dismiss them as unimportant, try to determine
their cause. (e.g.: Is the probe working properly?) Sometimes outliers
lead to new and interesting interpretations of the data. Were there
any outliers in the data you collected? Be prepared to explain how you
chose to handle outliers in your data analysis.
Endless
tables of numbers can be difficult to understand. A better method is
to present the data in a visual or graphical format (i.e.: Excel). Remember
that graphs don't have to display the origin. Often subtle and important
variations are only observable if the graph axes are modified to expand
the data in question (Figure below).

Also, take
advantage of Excel's multiple graphing ability (Figure below). It can
be very useful to display more than one graph at a time in order to determine
relationships between sets of data.

Interpretation
of Results
Consider the
following questions as you plan your poster and final presentation.
- Was data collected
by RUSS possibly affected by external factors?
- Is there sufficient
data to answer the research question ?
- What is the
best way to display the data?
- Are there
additional experiments to conduct?
- Did you
find any outliers? How can the outliers be explained?
- Are there
unanswered questions?
- Is there a
new research question?
Reporting
Results - Poster Format
Posters are
frequently used as means to display ongoing research and experimental
results. At scientific conferences, researchers gather in large auditoriums
to display their own work as well as examine the work of others. As individuals
circulate throughout the exhibits, they strike up conversations and exchange
ideas.
You will
display the results of your RUSS data analysis on a poster (Figure below).
The lengths of various sections will vary from one poster to the next.
Each poster will consist of no more than six 8.5" x 11" pieces of paper
glued to tag board (2 rows, 3 columns). Individual pages are arranged
to be read from left to right.

All posters
must contain the following, clearly labeled sections:
- Title -
An adaptation of the assigned research question.
- Authors -
Name(s)
- Introduction
- Introduce the research question, the data analyzed, and the analysis
plan.
- Results and
Discussion - Display only necessary data. Data presented must be discussed
in the text. Discuss data trends, correlations, and outliers.
- Conclusions
- Summarize the data analysis and compose the answer to the research
question. Are there additional experiments to conduct? Are there unanswered
questions?
Formatting
Notes
Text:
All text must
be in 24 point font except section titles that appear in 36 point font.
Lines should be double spaced with 0.5" margins (top/bottom/left/right).
Left justify all text. Use the spelling and grammar checker. Hand written
notes and comments are not allowed.
Graphs:
All graphs
must be clearly labeled. Use these labels when referring to graphs in
text (Example: Figure 1, Figure 2). Graph axis titles must be included
and correctly positioned. Hand written notes and comments are unacceptable.
Tables:
Data tables
must be properly titled. Columns and rows should be correctly labeled.
Hand written notes and comments are unacceptable.
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