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Look at the graph portraying the performance of value and growth stocks starting near the height of the two-tier market in 1971-72, a period very similar to the one we have today.
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We examined the graphs and articles to observe discrepancies with text, to observe efficiency of graph presentation, and to determine whether the graph portrayed unaggregated data.
The life graph portrays the whole time span from the end of the school (19 years) up to middle adulthood (52 years).
Instead of growing rapidly during the exponential stage, the graph portrayed low growth of bacterial cells (approximately fourfold lower) with extended lag phase compared to the untreated MRSA (control).
As we have discussed many times, the lines on graphs portraying trends do not represent real world temperatures; they represent *rates* of temperature change.
Much more impressive are the 1947 1960 graphs, portraying major transfers of mortality from ages under to ages over 55 for males and 60 for females, with reduction peaks in infancy and at ages 25 29.
Once we gathered all of our data and produced some preliminary graphs portraying number of mentions and specific needs, we established a smaller working group to make meaning out of the data and to make choices about the data on which we should focus.
These graphs portray trends in rare peak measurements in suspended particulate levels.
Figure 1 presents the direct acyclic graph (DAG) portraying the initial 'propositional' model put to testing.
Graphs infrequently portrayed by-subject data (9%) or advanced features (15%) such as pairing, symbolic dimensionality, or small multiples.
Well-designed graphs can portray complex data and relationships in ways that are easier to interpret and understand than text and tables.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com