Frequency polygons are advantageous in statistics as they provide a visual representation of data distribution, making it easier to identify patterns and trends. They also allow for easy comparison between multiple data sets. However, frequency polygons may oversimplify the data and obscure important details compared to other graphical representations like histograms. Additionally, they may not be suitable for very small data sets or when precise data values are needed.
In order to plot the points on either the frequency polygon or curve, the mid values of the class intervals of the distribution are calculated. Then the frequencies with respect to the mid points are plotted. However in a frequency curve the points are joined by a smooth curve, where as in a frequency polygon the points are joined by straight lines. Apart from this major difference, a frequency polygon is a closed figure where as the frequency curve is not.
A frequency curve is a graph obtained by joining the points of a frequency polygon freehand smoothly.
Yes, a frequency polygon is typically plotted by connecting points that represent the midpoints of each class interval in a frequency distribution. The points are plotted above the midpoints, with the frequency on the vertical axis and the class intervals on the horizontal axis. This visualization helps to show the shape of the distribution of the data. The polygon is often closed by connecting the endpoints to the horizontal axis at the minimum and maximum class intervals.
For ungrouped data.
A frequency polygon graph is used to visually represent the distribution of a dataset, highlighting the frequency of various values or intervals. It helps in identifying trends, patterns, and the shape of the distribution, making it easier to compare multiple datasets. Frequency polygons are also useful for detecting outliers and understanding the overall spread of data, and they can be used alongside histograms for a more comprehensive analysis.
A frequency polygon is not very effective in displaying group data when the class sizes are not the same.
In order to plot the points on either the frequency polygon or curve, the mid values of the class intervals of the distribution are calculated. Then the frequencies with respect to the mid points are plotted. However in a frequency curve the points are joined by a smooth curve, where as in a frequency polygon the points are joined by straight lines. Apart from this major difference, a frequency polygon is a closed figure where as the frequency curve is not.
The disadvantages of the polygon method include a lack of accuracy as well as detail. Advantages include its ease of use. The component method is much more exact, but is tougher to achieve.
One of the main advantages of using the polygon method is speed. The main disadvantage to this method is the fact that it cannot adequately represent curved items.
Dotplot allow you to identify original values
This is called a frequency polygon.
In a Frequency Polygon, a line graph is drawn by joining all the midpoints of the top of the bars of a histogram. A frequency polygon gives the idea about the shape of the data distribution. The two end points of a frequency polygon always lie on the x-axis.
A cumulative frequency polygon has straight lines connecting the points. A normal cumulative frequency diagram uses a smooth curve to join the points.
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By its very nature, measuring cumulative frequency on either axis of a graph will produce a continuing line on the opposite axis. Therefore, it is impossible to construct a closed frequency polygon when dealing with cumulative frequency.
A frequency curve is a graph obtained by joining the points of a frequency polygon freehand smoothly.
Identify the midpoint of the top of each bar of the frequency diagram. Join these together and they will form a frequency polygon. Sometimes the polygon is extended down to the horizontal axis to where the midpoints of the bar before the first bar would have been and where the bar after the last bar would have been.