Types of One-Dimensional Diagram

The bar uses a linear or one-dimensional foundation for comparison.’ Because just the length (height) of the bar (not the breadth) is considered in these diagrams, they are referred to as one-dimensional diagrams. Of course, the bar’s width or thickness have no bearing on the diagram; however, the thickness should not be excessive, or the diagram will appear two-dimensional.

Creating a Diagram: Some Pointers

When creating one-dimensional diagrams, remember the following guidelines:

1. All drawn bars should have the same width.

 (ii)  There must be a consistent spacing between each bar. 

(iii) All of the bars should have the same foundation.

(iv) The value of the variable represented by the bar should be written at the upper end of the scale so that the reader may comprehend the value without having to glance at the scale.

 (v) Each class interval has a frequency, relative frequency, or percent frequency. On the horizontal axis, draw a rectangle with the class interval as its base and the matching frequency, relative frequency, or percent frequency as its height.

(vi) The number of observations (frequencies, relative frequencies, or percentage frequencies) is scaled along the vertical axis while the value of variables (or class boundaries in the case of grouped data) is scaled along the horizontal axis. For graphical depiction of data sets, one-dimensional diagrams (charts) are used:

• A histogram 
• Polygon of frequency
• Curve of frequency
• Distribution of cumulative frequency (Ogive)
• Graph (pie)

Histograms 

These are a type of graph that shows how much information is contained (Bar Diagrams).Both ungrouped and grouped data are graphed with these diagrams. The values of the variable (the characteristic to be measured) are scaled along the horizontal axis of the graph, and the number of observations (or frequencies) are scaled along the vertical axis. To improve the contour of the distribution, the plotted dots are connected with straight lines. The number of observations in each class is represented by the height of these boxes (rectangles).

Mutual-funds histogram

The horizontal axis of the graph is used to specify the end points of class intervals, while the vertical axis is used to specify the number of observations (or frequencies). Rather than the end points of class intervals, mid-points are frequently presented on the horizontal axis. The width of each bar represents the class interval, while the height represents the frequency of observations in that class. Frequency Polygon

The frequency polygon is created by designating the midpoint at the top of horizontal bars and connecting them with a sequence of straight lines. Because the frequency polygons are produced as a closed figure with the horizontal axis, a series of straight lines are drawn from the mid-point of the top base of the first and last rectangles to the mid-point of the next outlying interval with zero frequency. In rare cases, the frequency polygon seems jagged.

Drawing vertical lines from the limits of the classes represented on the horizontal axis and linking them with horizontal lines at the polygon’s heights at each mid-point can also be used to transform a frequency polygon back into a histogram.

Sales-Related Subdivided Bar Chart

Cost, Revenue, and Profit/Loss Percentage Bar Chart

It is not always necessary to create a histogram before drawing a frequency polygon. Plotting points at heights equal to the matching class frequency above each class mid-point yields a frequency polygon. The polygon is then closed by connecting the points with a succession of straight lines, as previously demonstrated. The lower class limits are measured by the horizontal x-axis in this example, not the sequential class mid-points. The frequency polygon for the frequency distribution shown by the histogram in Figure 2.2 is shown in Figure 2.9.

Curves of Frequency

It can be characterised as a smooth frequency polygon. The

 (I) symmetry (skewness) and 

(ii) degree of peak ness of a frequency curve is used to define it (kurtosis).

Two frequency distributions can also be compared by superimposing two or more frequency curves if their class interval widths and total number of frequencies are comparable. Even if the distributions to be compared differ in total frequencies, they can still be compared by plotting percent frequency curves with the vertical axis measuring percent class frequencies rather than absolute frequencies.

Distribution of Cumulative Frequency (Ogive)

Rather than simply storing the number of observations inside intervals, it allows us to observe how many fall above or below specified values. Another data display technique that aids in data analysis and interpretation is cumulative frequency distribution. It displays the total number of observations below and above each class’s upper boundary.

Another way to visualise a cumulative frequency distribution is with an Ogive curve. 

The subsequent steps for designing the ogive curve are the same as before. The only difference is that the y-axis now needs to be scaled such that the entire frequencies may be accommodated. The upper class limits for less than ogive are labelled on the x-axis, while the lower class limits for more than ogive are labelled on the y-axis.

A pie chart

These diagrams are typically used to depict the total number of different sorts of observations in a data set as a percentage rather than an absolute amount through a circle. In a pie diagram, the highest percentage of data is usually shown first at 12 o’clock on the circle, followed by the other observations (in percent) in clockwise order in descending order of magnitude. The following are the stages of drawing a pie diagram:

(I) Multiply each of the data set’s observations (in percent) by 3.6 (360 100) to get the matching degrees in the circle.

(ii) Using a compass, draw a circle of appropriate size.

(iii) Using a protractor, draw points on the circle according to the size of each piece of the data and connect each of these points to the circle’s centre. The pie chart has two different advantages: 

          (I) it is aesthetically beautiful, and

         (ii) it demonstrates that the sum of all categories or pie slices equals 100%.

Conclusion

In this article, we learned a detailed explanation on types of one-dimensional diagrams. The most common sort of diagram used in practice is the bar diagram. A bar is a thick line whose width is only displayed to draw attention to it. One-dimensional bars are so named because only the length of the bar matters, not the width. To save space, lines may be drawn instead of bars when the number of elements is enormous.