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Unformatted text preview: ased should be presented in
an accompanying table.
4. The horizontal line measures time or independent variable and the
vertical line the measured variable.
5. Measurements proceed from left to right on the horizontal line and
from bottom to top on the vertical.
6. Each curve or bar on the chart should be labelled.
7. If there are more than one curves or bar, they should be clearly
differentiated from one another by distinct patterns or colours.
8. The zero point should always be represented and the scale intervals
should be equal.
9. Graphic forms should be used sparingly. Too many forms detract
rather than illuminating the presentation.
10. Graphic forms should follow and not precede the related textual
11.12.2 Line Graphs
The line graph is useful for showing changes in data relationship over a
period of time. In this graph, figures are plotted in relation to two intersecting
lines or axes. The horizontal line is called the abscissa or X-axis and the
vertical, the ordinal or Y-axis. The point at which the two axes intersect is
zero for both X and Y axis. The ‘O’ is the origin of coordinates. The two lines
divide the region of the plane into four sections known as quadrants that are
numbered anti-clockwise. Measurements to the right and above ‘O’ are
positive (plus) and measurements to the left and below ‘O’ are negative
(minus). is an illustration of the features of a rectangular coordinate type of
graph. Any point of plane of the two axes is plotted in terms of the two axes
reading from the origin ‘O’. Scale intervals in both the axes should be equal.
If a part of the scale is omitted, a set of parallel jagged lines should be used Sikkim Manipal University Page No. 168 Research Methodology Unit 11 to indicate the break in the scale. The time dimension or independent
variable is represented by the X-axis and the other variable by Y-axis. 11.13 Quantitative and Qualitative Analysis
11.13.1 Measures of Central Tendency
Analysis of data involves understanding of the characteristics of the data.
The following are the important characteristics of a statistical data: Central tendency Dispersion Skew ness Kurtosis In a data distribution, the individual items may hav...
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- Spring '10