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Interactive graphics: exemplified with real data applications.

Malik WA, Unlü A - Front Psychol (2011)

Bottom Line: Graphics are widely used in modern applied statistics because they are easy to create, convenient to use, and they can present information effectively.Static plots do not allow interacting with graphics.The benefits and strengths of interactive graphics for data exploration and data quality analyses are illustrated systematically with three complex real datasets.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of Augsburg Augsburg, Germany.

ABSTRACT
Graphics are widely used in modern applied statistics because they are easy to create, convenient to use, and they can present information effectively. Static plots do not allow interacting with graphics. User interaction, on the other hand, is crucial in exploring data. It gives flexibility and control. One can experiment with the data and the displays. One can investigate the data from different perspectives to produce views that are easily interpretable and informative. In this paper, we try to explain interactive graphics and advocate their use as a practical tool. The benefits and strengths of interactive graphics for data exploration and data quality analyses are illustrated systematically with three complex real datasets.

No MeSH data available.


Scatterplot of arrival delay by departure delay on the left. It shows many flights have much more arrival delay than departure delay. A few flights are delayed but arrived earlier than arrival time. The right-hand plot presents a zoom of lower left corner of left plot.
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Figure 7: Scatterplot of arrival delay by departure delay on the left. It shows many flights have much more arrival delay than departure delay. A few flights are delayed but arrived earlier than arrival time. The right-hand plot presents a zoom of lower left corner of left plot.

Mentions: Usually it is observed that arrival delay is highly associated with departure delay, the more the departure delay, the higher the arrival delay. High association between departure delay and arrival delay is visible in the left-hand scatterplot of arrival delay by departure delay in Figure 7. Bivariate outliers are visible from this scatterplot. Arrow 1 shows the flights that departed much after scheduled departure time but arrived before scheduled arrival time. Arrow 2 shows the flights which have a very high difference between departure delay and arrival delay. Zooming the values close to (0, 0) in the right-hand plot in Figure 7 shows clearly implausible values. For example, the arrow in the right-hand plot of Figure 7 shows a flight which departed with a delay of 1 min but arrived 91 min earlier than its scheduled arrival time.


Interactive graphics: exemplified with real data applications.

Malik WA, Unlü A - Front Psychol (2011)

Scatterplot of arrival delay by departure delay on the left. It shows many flights have much more arrival delay than departure delay. A few flights are delayed but arrived earlier than arrival time. The right-hand plot presents a zoom of lower left corner of left plot.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3111423&req=5

Figure 7: Scatterplot of arrival delay by departure delay on the left. It shows many flights have much more arrival delay than departure delay. A few flights are delayed but arrived earlier than arrival time. The right-hand plot presents a zoom of lower left corner of left plot.
Mentions: Usually it is observed that arrival delay is highly associated with departure delay, the more the departure delay, the higher the arrival delay. High association between departure delay and arrival delay is visible in the left-hand scatterplot of arrival delay by departure delay in Figure 7. Bivariate outliers are visible from this scatterplot. Arrow 1 shows the flights that departed much after scheduled departure time but arrived before scheduled arrival time. Arrow 2 shows the flights which have a very high difference between departure delay and arrival delay. Zooming the values close to (0, 0) in the right-hand plot in Figure 7 shows clearly implausible values. For example, the arrow in the right-hand plot of Figure 7 shows a flight which departed with a delay of 1 min but arrived 91 min earlier than its scheduled arrival time.

Bottom Line: Graphics are widely used in modern applied statistics because they are easy to create, convenient to use, and they can present information effectively.Static plots do not allow interacting with graphics.The benefits and strengths of interactive graphics for data exploration and data quality analyses are illustrated systematically with three complex real datasets.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of Augsburg Augsburg, Germany.

ABSTRACT
Graphics are widely used in modern applied statistics because they are easy to create, convenient to use, and they can present information effectively. Static plots do not allow interacting with graphics. User interaction, on the other hand, is crucial in exploring data. It gives flexibility and control. One can experiment with the data and the displays. One can investigate the data from different perspectives to produce views that are easily interpretable and informative. In this paper, we try to explain interactive graphics and advocate their use as a practical tool. The benefits and strengths of interactive graphics for data exploration and data quality analyses are illustrated systematically with three complex real datasets.

No MeSH data available.