Getting expertise in the graphical presentation of data is important and also the major way to get insights about data.
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Graphical Presentation of Data
A chart/ graph says more than twenty pages of prose, it is true when you are presenting and explaining data. The graph is a visual display of data in the form of continuous curves or discontinuous lines on graph paper. Many graphs just represent a summary of data that has been collected to support a particular theory, to understand data quickly in a visual way, by helping the audience, to make a comparison, to show a relationship, or to highlight a trend.
Usually, it is suggested that the graphical presentation of the data should be carefully looked at before proceeding with the formal statistical analysis. It is because the trend in the data can often be depicted by the use of charts and graphs.
A chart/ graph is a graphical presentation of data, in which the data is usually represented by symbols, such as bars in a bar chart, lines in a line chart, or slices in a pie chart. A chart/ graph can represent tabular numeric data, functions, or some kinds of qualitative structures.
Common Uses of Graphs
Graphical presentation of data is a pictorial way of representing relationships between various quantities, parameters, and variables. A graph summarizes how one quantity changes if another quantity that is related to it also changes.
- Graphs are useful for checking assumptions made about the data i.e. the probability distribution assumed.
- The graphs provide a useful subjective impression as to what the results of the formal analysis should be.
- Graphs often suggest the form of a statistical analysis to be carried out, particularly, the graph of model fitted to the data.
- Graphs give a visual representation of the data or the results of statistical analysis to the reader which are usually easily understandable and more attractive.
- item Some graphs are useful for checking the variability in the observation and outliers can be easily detected.
Important Points for Graphical Presentation of Data
- Clearly label the axis with the names of the variable and units of measurement.
- Keep the units along each axis uniform, regardless of the scales chosen for the axis.
- Keep the diagram simple. Avoid any unnecessary details.
- A clear and concise title should be chosen to make the graph meaningful.
- If the data on different graphs are to be measured always use identical scales.
- In the scatter plot, do not join up the dots. This makes it likely that you will see apparent patterns in any random scatter of points.
- Use either grid rulings or tick marks on the axis to mark the graph divisions.
- Use color, shading, or pattern to differentiate the different sections of the graphs such as lines, pieces of the pie, bars, etc.
- In general start each axis from zero; if the graph is too large, indicate a break in the grid.
For further reading about the Graphical Presentation of data go to https://en.wikipedia.org/wiki/Chart
Graphical Presentation of Data in R Language
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