Some random thoughts on how to keep your figures flattering.
Use scatterplots to show relationships (correlations) between continuous variables. Correlations say nothing about causality. You can provide a correlation coefficient and statistical significance either in the figure legend (you wouldn’t do that in a manuscript, however) or directly next to your cloud of points so that reader doesn’t need to hunt through your figure legend or results text to find out why the graph is being show…make it easy on your poster visitor.
Use regression plots to display how one variable causes variation in a second variable (on Y-axis). As for correlation analysis, you can put the details in the figure legend, but it’s better to situate your findings in a graphical way on your graph. For example, you could put the statistical outcomes on graph in red, along with a phrase in English describing why reader should care. Make the data points bold and large so that the focus of the plot are the data not line (that’s my preference).
Purrington, C.B. Watch your figures. Retrieved YYYY-MM-DD from https://colinpurrington.com/tips/figures.
For those who might be interested, the graphs are all sketched out with Omnigraffle.