Category:Graphs, charts, diagrams: Difference between revisions
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Graphs are to visualize quantitative data and relationship between variables using a system of coordinates. They are powerful in getting the message across, but the same data can be displayed in many ways, with a variety of visual effects. Examples include line graphs, histograms, and bar graphs. These graphical tools help us to see magnitude, trends, differences and similarities in the data. They are a key aspect in scientific communication for any audience. There is no general advice about when it is appropriate to use a graph rather than a table. Graphs offer the opportunity to show more data, and thus are most suited for data that cannot be easily displayed in a table <Ref name="Altman">Altman DG. Practical statistics for medical research. London: Chapman & Hall; 1991. p. 43.</ref>. This is often the case when there is a trend or comparison to be shown <Ref>McLennan W. 1331.0 Statistics - a powerful edge! 2nd ed. Australian Bureau of Statistics; 1998. p. 103.</ref>. Some displays, such as histograms, are in essence graphical <Ref name="Altman"/> | |||
Graphical displays should: | |||
* show the data | |||
* induce the viewer to think about the substance rather than about methodology, graphic design, the technology of graphic production, or something else | |||
* avoid distorting what the data is telling | |||
* present many numbers in a small place | |||
* make large data sets coherent | |||
* encourage the eye to compare different pieces of data | |||
* reveal the data at several levels of detail, from a broad overview to the fine structure | |||
* serve a reasonably clear purpose: descriptions, exploration, tabulation, or decoration | |||
* be closely integrated with the statistical and verbal descriptions of the data set <Ref>Tufte ER. The visual display of quantitative information. 2nd ed. Connecticut: Graphics Press; 2009. p. 13</ref> | |||
In this part of the FEMWIKI, the use of [[line graphs]], [[histograms]], [[frequency polygons]], [[bar graphs]], [[Pie charts|pie graphs]], and [[other types of data display]] are discussed. | |||
=References= | |||
<References/> | |||
==FEM PAGE CONTRIBUTORS 2007== | |||
;Editor | |||
:Agnes Hajdu | |||
;Original Author | |||
:Alain Moren | |||
;Contributors | |||
:Lisa Lazareck | |||
:Maarten Hoek | |||
:Agnes Hajdu | |||
[[Category:Informing Action / Improving Knowledge]] | [[Category:Informing Action / Improving Knowledge]] | ||
Latest revision as of 08:11, 29 March 2023
Graphs are to visualize quantitative data and relationship between variables using a system of coordinates. They are powerful in getting the message across, but the same data can be displayed in many ways, with a variety of visual effects. Examples include line graphs, histograms, and bar graphs. These graphical tools help us to see magnitude, trends, differences and similarities in the data. They are a key aspect in scientific communication for any audience. There is no general advice about when it is appropriate to use a graph rather than a table. Graphs offer the opportunity to show more data, and thus are most suited for data that cannot be easily displayed in a table [1]. This is often the case when there is a trend or comparison to be shown [2]. Some displays, such as histograms, are in essence graphical [1]
Graphical displays should:
- show the data
- induce the viewer to think about the substance rather than about methodology, graphic design, the technology of graphic production, or something else
- avoid distorting what the data is telling
- present many numbers in a small place
- make large data sets coherent
- encourage the eye to compare different pieces of data
- reveal the data at several levels of detail, from a broad overview to the fine structure
- serve a reasonably clear purpose: descriptions, exploration, tabulation, or decoration
- be closely integrated with the statistical and verbal descriptions of the data set [3]
In this part of the FEMWIKI, the use of line graphs, histograms, frequency polygons, bar graphs, pie graphs, and other types of data display are discussed.
References
- ↑ 1.0 1.1 Altman DG. Practical statistics for medical research. London: Chapman & Hall; 1991. p. 43.
- ↑ McLennan W. 1331.0 Statistics - a powerful edge! 2nd ed. Australian Bureau of Statistics; 1998. p. 103.
- ↑ Tufte ER. The visual display of quantitative information. 2nd ed. Connecticut: Graphics Press; 2009. p. 13
FEM PAGE CONTRIBUTORS 2007
- Editor
- Agnes Hajdu
- Original Author
- Alain Moren
- Contributors
- Lisa Lazareck
- Maarten Hoek
- Agnes Hajdu
Pages in category "Graphs, charts, diagrams"
The following 6 pages are in this category, out of 6 total.