In order to analyze the numerical data and the frequency of the collection, the graphical forms make the basis of representation. The graphical representations are easy to understand and assess. One such graphical tool showing the frequency distribution of each value of the data is a histogram. The concept forms an important part of statistics and data handling.
Table of Contents
Histogram can be understood as a diagrammatic and graphical representation that consists of rectangles which have area proportional to frequency and width is same as the extent of class interval. The representation organized the group of data points. Though the appearance is similar to the bar graph actually it is not. Histogram can be defined as the representation of grouped frequency distribution according to the class intervals.
The representation is a famous statistical pictorial tool used to summarise data on an interval basis. Often used to give the descriptive data in detailed and precise ways histogram makes the understanding of the concept simple. The frequency and the length (height) of the histogram are proportional and dependant.
The graph (histogram) works under certain necessary conditions, which are:
- Numerical data.
- Analysis of data distribution is to be worked.
- The change in process from a period to the other.
- Determination about the output.
- Analysis of customer needs according to the process preferred.
- When the processing of data is to be analysed.
A histogram is a representative 2-D figure while the bar graph is a representation in a single dimension.
In a histogram, the area of rectangles gives the measurement of frequency while the length of the bar graph gives frequency but in this width doesn’t get any importance.
The rectangles of the histogram are continuous and joined whereas the bar graphs are separated from each other by continuous and equal spaces.
The given differences can be assessed by anyone after analysing the pictorial representation of both.
The classification is basically made on the basis of the distribution of frequency. Even the distributions are classified as normal, skewed, bimodal, multimodal, comb, edge peak, etc. The various types of histograms can be named uniform histogram, symmetric, probability, and bimodal histogram.
This type of histogram is applied in the case of small class intervals and approximately the same frequency of data and the involvement of several peaks. Such representation reflects the consistency in the data.
As the name itself suggests such a histogram shows two models of the histogram on the same graph. Such graphical representations are used to show different data’s or compare the two different kinds of information. Both the histogram shows independent data with a gap between the two.
The histogram is symmetric if the y-axis of the histogram and two sides of the same are identical both in shape and size. The representation showing a perfect symmetry is called an asymmetric histogram. (Being symmetric means the left half of the graph is identical to the right half of the same histogram)
The probability representation is represented by a probability histogram. The corresponding probability of the data is the same as the area of each rectangle. The length (height) of the histogram gives the results of probability. The histogram is started by the selection of class intervals.
The following steps make the construction of the histogram simple and easy.
- Mark the class intervals on the horizontal line (x-axis) and frequency on the vertical axis (y-axis).
- Mark the identical scales on both the axis.
- Prefer the intervals exclusive in nature.
- Start construction of rectangles according to the class size and intervals and related data (frequency) as heights.
- The height of the figures shows the respective frequency and the intervals are taken equal.
In order to have a better understanding of the topic download Cuemath today. The app also helps you explore various other concepts like linear graph. A straight-line graph is known as a linear graph. This type of graphs represents linear two variable equations that show the relation of two quantities.