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How to Create Outstanding Engineering Graphs

for Reports and Presentations

IntroductionThe primary purpose of a technical graph is to tell a story.

An outstanding graph presents a large data set in a small

space such that a reader can identify trends, understand

relationships between variables, and grasp an idea quickly.

Very often, the reader will be a supervisor, purchasing

agent, attorney, or other individual who lacks your

technical background. Well-designed graphs tell a story

better than text can, and will enhance your technical

credibility.

Microsoft Excel is the most widely used graphing softwarein engineering and technology because it is ubiquitous in

the workplace. However, Excel was designed for business,

not technology, so many of its default settings are business-

oriented. For example, many financial graphs (charts in

ExcelSpeak) present quarterly results, in column form.

Excels ChartWizard directs you first to column graphs,

then to line graphs (which are column graphs without the

columns). Both column and line graphs plot a variable vs. a

category. These categories are evenly spaced along the

horizontal axis. The fifth choice is the x-y (scatter) graph,

which shows the relationship between two continuouslyvarying variables. If you select a line graph to plot x-y data,

the results can be misleading.

Pie charts, line graphs, bar charts, and their ilk are regarded

as little more than cartoons by the engineering community.

6.0 7.1 7.2 8.4 6.0 7.0 8.0 9.0

Excel line graph

spaces the data at

equal intervals .

The same data on

an x-y graph tells a

different story

Identify the Variables

In a physical test, the input is the Independent Variable.

The output, or result of the test, is the Dependent Variable.

In almost every case, the Independent Variable is plotted on

the horizontal axis (x-axis), while Dependent Variables are

plotted on the vertical axis (y-axis). A significant exception

to this rule is the stress-strain curve, where an applied load

(input = stress) causes a test specimen to stretch (output =strain).

When you graph A vs. B, remember that A is the dependent

variable, and B is the independent variable.

Independent Dependent

Input Output

Body rustFluid flow rate

Tread depth

Fatigue life

Exam grade

TC voltage

Cars ageValve setting

Tire mileage

Fillet diameter

Study time

Temperature B

A

A vs. B

Points and Lines

The convention for technical graphs is to plot data as

points. Use lines for theory, for regression lines (curve

fitting), or for clarity (connect the dots).

data points data & lines no data

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Titles

The purpose of a title is to describe what is being plotted. It

may seem redundant to describe the graph in the text of a

report, then describe it in a title. However, graphs are more

likely to be borrowed from your report than your text.

When your graph lands in someone elses report or

presentation, the title provides context.

Label the axes with the name of the variable, followed by

the units in parentheses. For example: Temperature (F).

Even better: Bath temperature (F).Age (years)

Height

(m)

Average height of mapletrees on IPFW campus,

summer 2004

Age

Height

Regression Lines

Never extrapolate beyond the range of the actual data,

unless you clearly label the extrapolation as a guess, and

clearly distinguish the extrapolation line from all other

lines.

Use an appropriate nonlinear regression if justified by the

math, not just because it looks good. For example, sound

level is a function of the logarithm of the distance from thesource. Do not use an exponential function to fit the data,

even if it looks betterthe math does not support it.interpolation extrapolation = wild guess

Grid Lines

Excel automatically inserts horizontal grid lines. If you

choose to include grid lines, make sure the final product is

easy to read. Generally, it is best to remove the grid unless

you plan to read data off the graph.

clean & gridless overwhelmingExcel default

Legend

Excel automatically inserts a legend, labeling each data set

(series in ExcelSpeak) in numerical order. If you have

one set of data, delete the legend.

Series 1

Delete!

The order of symbols in a legend should parallel the

arrangement of the data in the graph. For example, the

topmost legend symbol should stand for the topmost line on

the graph. A parallel structure is clearer, and helps the

reader understand the graph more quickly.

Chickens

Pigs

Ducks Chickens

Pigs

Ducks

not

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In many cases, it is better to label the data directly on the

graph, rather than use a legend. Symbols, colors, and line

thicknesses become confusing beyond four or five datasets,

especially if the graph will be printed in black & white.

Street names and route numbers are marked directly on the

roads on a conventional map. No mapmaker would

consider placing street names and route numbers in a longlegend at the side of the map, yet we do this routinely with

technical graphs, at the expense of readability.

Chickens

Pigs

Ducks

Look ma, no legend!

10

Direct labeling beats a

7-element legend

20

30

40

5060

70

Range

Select ranges sensibly. Excel automatically sets the origin

at (0,0), but you may need a different origin to show

variations in the data. For example, if the voltage from a

thermocouple varies from 46 to 49 mV, scale the axis to 45-

50, not 0-50 mV. The two graphs at the right contain the

same data, but tell different stories.

45

The data ranges

from 46 to 49 mV

Adjust the range to see

the true relationship

50

0

50

VT(mV)

Comparison

A good graph shows values and trends; a better graph

enables the reader to compare different sets of data.

Comparisons occur between multiple sets of data on the

same graph, and between multiple graphs presented side-

by-side (as in the annual automotive issue of Consumer

Reports magazine).

If you plot multiple sets of data on different graphs,

consider using the same ranges on the axes. The reader will

find it easier to draw comparisons. For example, if the

student weights at the right were plotted from 80 to 180 lb.,

and the parent weights were plotted on an adjacent graph

from 120 to 220 lb., the variation in parent weights would

still be apparent, but the differential would disappear.

This data set shows a

general trend, with

some scatter .

Now we have two data

sets to compare .

Parents weigh more,and vary more.

Height

Weight vs. height ofhigh school students

Students

Parents

Weight vs. height of high

school students & theirparents

Weight

Conclusion

Once your graph is complete, ask the following questions:

Is everything readable? Is the legend parallel to the data? Is the regression analysis appropriate? Are trends easy to spot? Is it easy to compare different sets of data?

Above all, ask:

Does it tell a story?