Getting Smart About Posters and Slides

January 20, 2016

Complicated or unclear graphs and data plots are where valuable research gets lost. Don’t let this happen to you. Your research should live in graphs and data plots that ensnare audiences and engage professionals. We are here to teach you how to build the effective, meaningful and eye-catching graphics your research deserves.

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Use The Right Kind Of Plot For Your Data

An effective chart is a beautiful chart. But, it’s important to display data in the most clear and effective way.

  • Pictures define features in an image with a legend.
  • Line graphs are best used for data with one continuous variable.
  • Scatter plots are best used for XY coordinate data.
  • Bar charts are best used for categorical data. Note that a vertical orientation is preferred.
  • Proportional charts are best used to represent parts of a whole, but work best with only a few groups.
  • Box and whisker plots are useful to highlight population differences and identify possible outliers.
  • Contour plots are useful for multi-dimensional data and are very effective with color.

Figures Should Elucidate Information, Not Obfuscate

Your data are your data. Do not manipulate it to emphasize or disguise trends. Also, do not manipulate your figure to (de)emphasize observations. Use the same scale for similar data sets and remember that your graph should be styled to reflect the design of the experiment.

Apply Principles Of Effective Formatting

Keep these design principles in mind while creating your chart/plot:

  • Neatness: Image is clean, sharp and invites attention
  • Readability: The eye can discern important information quickly and easily
  • Font: Text is sans-serif, large enough to read and placed well
  • Size: Graph is sized appropriately for anticipated reduction during printing
  • Aesthetics: Graphs are balanced with good use of white space, drawing the eyes to the most important features
  • Use of color: Distinguishes important content and is pleasing to the eye
  • Consistency: Similar graphs have same stylistic scheme (line width, font type and size, labeling, scales, etc.)