Histogram And Its Application

Statistics is defined as the study of data collection, organisation, analysis, interpretation, and presentation. It is customary to begin with a statistical population or a statistical model to be studied when applying statistics to a scientific, industrial, or social problem. 

In statistics, bar graphs, histogram, and linear graphs are used commonly. Let’s go through the meaning of histograms. 

A histogram is a collection of rectangles with bases and intervals between class boundaries. Each rectangle bar represents some kind of data, and they are all adjacent. Rectangle heights are proportional to corresponding frequencies of similar and different classes.

How Do You Create a Histogram?

The following steps will walk you through the process of creating a histogram from the given data:

Step 1: Select an appropriate scale to represent weights on the horizontal axis.

Step 2: Select an appropriate scale for representing the frequencies on the vertical axis.

Step 3: Using the frequencies of the given weights, draw the bars that correspond to them.

When to Use a Histogram?

• The information is numerical.
• When determining whether the output of a process is distributed approximately normally, you want to see the shape of the data’s distribution.
• Determining whether a process can meet the needs of the customer
• Examining how the output of a supplier’s process appears
• Determining whether a process change occurred from one time period to the next
• Determining whether two or more processes’ outputs differ
• You want to quickly as well as easily communicate the distribution of data to others.

Applications of Histogram

A histogram is one of the best formats for displaying analysis, whether you are selecting a representative for your country or conducting a simple opinion poll. It is important to note that the graphical representation of votes received by a specific candidate or party is a bar graph, not a histogram, because one of the axes in such a graph represents the candidate, rather than a numerical class interval. 

Nonetheless, data scientists and statisticians use histograms to display a variety of numerical evaluations, such as the vote fraction of a specific party in all polling stations, the distribution of the number of valid votes per polling station, the distribution of the number of people involved in election campaigns, voter arrival time analysis, and so on. All of these factors, when visualised using histograms, assist candidates and political parties in developing better election strategies.

What is a Linear Graph?

A linear graph is represented by a straight line. A graphical representation is used to demonstrate the relationship between two or more quantities. A linear graph is one in which any relation’s graph yields a single straight line. A straight line is referred to as a “linear.” A straight line graph drawn on a plane that connects points plotted on the x and y coordinates is known as a linear graph. Do you find Linear graphs and histograms interesting? Visit Cuemath to learn more.

Important Reminders:

• Two pairs of (x,y) are required to plot a linear graph. But we won’t know if there was an error in calculating these values because two points can always be joined to form a line. It is recommended that another point be plotted to ensure that the solutions obtained for the given linear equation are correct.
• The equation y = kx (where k is a real number) represents a horizontal line parallel to the X-axis.
• The equation x = ky (where k is a real number) represents a vertical line parallel to the Y-axis.

Hints and Tips!

The following are a few important tips and tricks to keep in mind when visualising any data with a histogram.

• While drawing a histogram, select the scale on the vertical axis and look for the highest number that divides all the frequencies. If no such number exists, look for the highest number that divides the majority of the frequencies.
• A histogram is a type of graph that summarises continuous data.
• A histogram is a visual representation of continuous data.
• The scales of both the horizontal and vertical axes do not have to begin at 0.
• A histogram should have no gaps between its bars.