Know how line graphs mislead.

1. LINE GRAPHS
Travel in your time…
into the world of

2. What on earth are they
A line graph is commonly used to display information as a series
of data points connected by straight line segments on two axes.
The line graph therefore helps to determine the relationship
between two sets of values, with one data set always being
dependent on the other set.
Line graphs are drawn so that the independent data are on the
horizontal X-axis (e.g. time) and the dependent data are on the
vertical Y-axis. Line graphs are used to track changes over short
and long periods of time. There is some debate about the degree
of measurement between time points. Some say the data must
be measured nearly continually in order for the lines to be
accurate representations. Others feel a monthly measurement is
sufficient, even though the line implies data at points where no
measurement was taken.

3. Line Graphs and Cropping----
1. Line graphs are typically used for time-based
analysis, especially trend analysis.
2. However, its accuracy might be affected by the
distortions caused to it.
3. DISTORTIONS
• Choosing a smaller choice of data can often lead to the
misinterpretation of the target set.
• The second type of distortion is the change of scale of
data on the Y-Axis. If this coordinate hasn’t a reduced
scale, then it is possible that it doesn’t show much
variation. This could also mislead our inferences. This
larger scale implies cropping of the possible variations
in a data set.

4. Examples of Scale Distortions
58.5
59
59.5
60
60.5
61
1-Jul 2-Jul 3-Jul 4-Jul 5-Jul 6-Jul 7-Jul 8-Jul
Variation in Dollar-Rupee Exchange Rate in July 2013
Price of Dollar in
Rupees

5. 0
10
20
30
40
50
60
70
1-Jul 2-Jul 3-Jul 4-Jul 5-Jul 6-Jul 7-Jul 8-Jul
Variation in Dollar-Rupee Exchange Rate in July 2013
Price of a Dollar in
Rupees

6. CONCLUSION
So as we see, the reduction of scale on the y-axis results in the
cropping of vital information which is of course the variation in
Dollar-Rupee Exchange Rate over the first 8 days of July’13.
Therefore, to maintain the accuracy of the data set, it is important
that we account for its change pattern; how stable it is. This is
possible through expansion of the scale of the coordinate; i.e.
y-axis.

7. A PRESENTATION
BY
SRISHTI
FC-SEC N
419, ECO(H)