Graphing Scientific Data
From a
Mathematics Across the Curriculum (MAC)
coordinated studies class
with Biology 201 (Fall 2000)
at Edmonds Community College
Melissa Mackay (Math)
Jenny McFarland (Biology)
Why?
• Most students in science courses know how
to graph
Why?
• Most students in science courses think they
know how to graph
• This exercise lets them discover what they
know and don’t know
• Self-assessment is used
• Result – better graphs!
Learning Outcomes
• Define terms
• Students create and assess graphs
– Students create graphs in small groups
– Critique graphs in large group
• Students develop graphing rubric
• Students practice self-assessment
– Self-assess graphs in lab reports
• Students choose appropriate graphs for particular
data sets
– Scatter plots & line graphs
– Bar graphs & histograms
– Pie charts
Define the following terms:
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dependent variable
independent variable
scatter graph
line graph
bar graph
pie graph or chart
best fit line
slope
interpolation
extrapolation
Group Exercise
• For the set of data assigned, create a
graph/chart that you think best displays the
data.
• Use the graph paper (if needed) and colored
pencils
• Groups will share graphs with large group.
Data
Graphing Rubric/Criteria
• Students in class or lab session develop rubric
– Appropriate, descriptive title
– Axes
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dependent & independent variables on correct axes
labels
units
good scaling
– Clear data points (easy to differentiate different symbols)
– Key (if plotting more than one set of data)
– Appropriate line-fitting
• best-fit line
• curve-fitting
• connecting dots
– Use graph paper or computer-generated graphs
Student Self-assessment
Student self-assessment
– is crucial to student learning
– requires students to understand assessment criteria
– requires that students do some critical analysis of their work,
usually improving the product
– allows students to take responsibility for their work
– empowers students - so they know when they have
performed well and do not rely on the instructor’s
assessment alone
Self-assessment example
From Biology 201 Photosynthesis Lab report:
– Graph the absorbance spectra measured in your lab
session.
– What type of graph did you use? Why? (Explain your graph
choice.)
– Evaluate your graphs for this lab report. Are they excellent,
adequate or poor? Can a reader look at this graph and
know what you did? What criteria are you using to evaluate
your graphs? Be explicit; list the criteria and state how you
met each one.
Bad Graphs - Scaling
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Bad scaling is a common problem in
student graphs.
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Students often need to see several
examples. Presenting opportunities for
students to assess graphs with bad
scaling will help them recognize this and
give them practice with better scaling
alternatives.
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From: “Making Graphs”
http://scipp.ucsc.edu/~mothra/ta/graph/graph.ht
ml
Bad Graphs - missing information
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What is missing? Students often have information missing from their graphs.
Self-assessment helps students catch these omissions.
This problem is complicated by missing information in many textbook figures,
where graph axes might not be labeled or may not have units.
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From: http://www.ecs.umass.edu/ece/ece211/ECE211_graphing_techniques.html
Bad Graphs - area
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Multidimensional variation occurs where
two-dimensional figures are used to
represent one-dimensional values. The
size of the graphic is scaled both
horizontally and vertically according to
the value being graphed. This results in
the area of the graphic varying with the
square of the underlying data, causing an
exaggerated effect in the graph.
This graph has a lie factor of about 2.8,
(variation between the area of each
doctor & the number it represents).
Students do not usually generate this
type of graph, but they often see it in the
media.
From: Pitfalls of Data Analysis (or How to Avoid
Lies and Damned Lies) by Clay Helberg, M.S.
Tufte, E.R. (1983). The Visual Display of
Quantitative Information. Cheshire, CT:
Graphics Press. p. 69