Definition of Histogram Examples
A histogram is a statistical tool for the representation of the distribution of the data set. It is a general estimation of the probability distribution of a continuous series of variable data. It is actually a plot that answers all the queries with the underlying frequency distribution of a set of continuous and probable data, it gives a sense of the density of data. In a histogram, the frequency of occurrences for each bin is indicated by the area of the bar. In this article, we are going to provide you with top examples of a histogram graph.
Examples of Histogram graph
There are many examples of the histogram. Some of them are:-
- Bimodal
- Symmetric, Unimodal
- Skewed Right
- Skewed Left
- Multimodal
- Symmetric
1. Bimodal Histogram
When a histogram has two peaks, it is called a bimodal histogram. It has two values that appear most frequently in the data set.
Example 1
Like many restaurants can expect a lot more customers around 2:00 pm and 7:00 PM than at any other times of the day and night. This makes the histogram graph a bimodal since there are two separate time periods during the whole day that correspond to two peak serving times for the restaurant.
Example 2
In India, people tend to do their grooming at weekends. So, if we depict a histogram for all 7 days visit of people to parlors and salon, Saturdays and Sundays would be two extremes. The data distribution would be somewhat like below:
2. Symmetric, Unimodal Histogram
A histogram is unimodal if there is only one hump. This means that the frequency of occurrence of an event is spread in a manner where there are no extremes.
Example 1
Professor Brook wanted to see and count hours spent by his students for the coming test. He came up with the following numbers: 1, 3, 2, 1, 5, 1, 4, 3, 2, 1, 1 where each number represents the number of hours each student spent for study. The same data is represented in a bar chart and we can see a fair balance between left and right tails.
3. Skewed Right Histogram
It is the histogram where very few large values are on the right and most of the data are on the left side, such data are said to be skewed to the right. They are also known as positively-skewed distributions.
Example 1
In tough exams, it’s always difficult to get great marks to say more than 90%. However many students manage to get fair marks.
Example 2
Usually, there is a very large difference between wealthy, average, and poor people. The wealth of people in a country is concentrated in a few hands and the rest of the population are living in a dearth of money. It has its natural boundary at zero. The graph in both cases will be somewhat like below:
4. Skewed Left Histogram
It is the histogram where very few large values are on the left and most of the data are on the right side, such data are said to be skewed to the left. They are also known as negatively skewed distributions. That’s because there is a long elongated tail in the negative direction.
Example 1
In any general office, employees tend to drink less tea or coffee, but as a later hour approaches, their tiredness increases and they tend to drink more tea and coffee. Such data can be represented by the Skewed left histogram as shown in the graph below.
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Example 2
In a company, there are many employees with higher, middle, and operational level jobs.
Their salary also varies in the same manner. The graph for the same data would be somewhat like the below histogram:
5. Multimodal Histogram
In a histogram where a multimodal distribution is shown as a continuous probability distribution with two or more modes. In a multimodal histogram, we get to know that the sample or data is not homogeneous an observation or conclusion comes as overlapping distribution.
Example 1
Suppose a survey is done amongst 50 youth of the millennial generation as to what they are following currently amongst GOT, Marvels, DC, IPL, upcoming World Cup, the answer could be an extreme of two or more.
Example 2
Jorge as a branch manager decided to work on the time that any customer wait to get their work done at banks. After a survey with 10 customers, he got the result as 5, 8, 20, 10, 3, 6, 12, 25, 9, 11(in min). The graphical distribution for the same data would be somewhat like the below histogram:
6. Symmetric Histogram
In a histogram, if they have the same shape on both sides of the medium, the data are symmetric. The two side looks the same if the histogram is folding in between.
So, asymmetric distribution is a data distribution where one of the two halves appears as a mirror image of another half.
Example 1
If we do a survey amongst 25 male for the measurement of their weights and heights, the data often follow the pattern of symmetric distribution. Data of most people will fall within a certain amount of the typical value with few extremes in either direction.
Example 2
Suppose XUZ Pvt. Ltd is a company where each 15 employee spends these money fro lunch: $10, $5, $15, $23, $7, $9, $11, $18, $13, $4, $12, $8, $15, $3, $8.5. The graph fro the same data will be like below graph.
Conclusion – Histogram graph Examples
The histogram provides a visual interpretation of numerical data. It is done by showing the number of data points that fall within a specified range of values which is knowns as bins. So, we see that there could be innumerable examples of histogram from our daily life. There could be many histograms from the same set of data with different purposes and situations. The histogram is a very useful tool for database interpretation.
The histogram is very important as it displays a large amount of data and the frequency of the data values. Also, the median and distribution of the data can be determined by a histogram. Apart from this, it can show outliers or gaps in the data, if any. Histogram charts convey information about data set faster than tables.
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