 # Histogram

A histogram meaning can be stated as a graphical representation that condenses a data series into an easy interpretation of numerical data by grouping them into logical ranges of different heights which are also known as bins. Basically, it summarizes discrete or continuous data. We can also call it a frequency distribution graph as it is like a plot that lets you discover the underlying frequency distribution.

Histogram definition can be put forward as a tool that visualizes the distribution of data over a continuous interval or a certain time period. It helps us to get an estimate of where the values are concentrated, what are the extremes if there is any gap or unusual values. To some extent, a histogram also gives us a brief view of a probability distribution. A histogram is quite similar to a vertical bar graph but the difference that lies between them is that there is no gap between the bars in the histogram, unlike a bar graph.

Characteristics Of A Histogram

1. A histogram is used to display continuous data in a categorical form.

2. In a histogram, there are no gaps between the bars, unlike a bar graph.

3. The width of the bins is equal.

### Parts Of A Histogram

A histogram can be divided into several parts. These parts make up a complete histogram.

1. The Title: The most important part is the title of a histogram. The title tells us what the histogram is about. In other words, it describes the information provided in the histogram.

2. The X-axis: It is an interval that represents the scale of values which the measurements fall under.

3. The Y-axis: It represents the frequency of values occurring within the intervals set by the X-axis.

4. The Bars: The last is the bars whose height represents the number of times that the values occurred within the interval while the width of the bar shows the interval that is covered.

### How Histograms Work

To know how to make a histogram, you need to know that histograms are useful in statistics to illustrate how many of a certain type of variable occurs within a specific range. Let's take an example, a histogram is used to focus on the demography of a country to exhibit how many people are between the ages of 0 to 10, 11 to 20, 21 to 30, and 31 to 40 and so on… the X-axis will represent the demography while the Y-axis will represent the age of the people.

### It Is The Area, Not The Height Of The Bars

In a histogram, it is the area and not the height of the bar that indicates the frequency of occurrences for each bin. The height of the bar does not indicate how many occurrences of scores are there in each individual bin. It is always the product of height and width of the bin that indicates the frequency of occurrences within that bin.

### How To Create A Frequency Histogram Graph

To construct a histogram graph from a continuous variable there are few steps that we need to follow. They are given below;

Step 1) Firstly, we need to split the data into class intervals which are also known as bins and frequencies.

Step 2) In this step, we have to draw a histogram graph with X-axis and Y-axis. Then write down the class intervals on the X-axis and the frequencies on the Y-axis.

Step 3) Draw vertical rectangles using the X-axis and the Y-axis.

## Difference Between Bar Graph And Histogram

 HISTOGRAM BAR GRAPH Indicates Distribution of non-discrete variables Comparison of discrete variables Represents Quantitative data Categorical data Spaces No spaces between the bars Spaces are there between the bars Elements Elements are grouped together Elements are taken individually Reordering of bars No Yes Width of the bar Doesn’t need to be same Has to be same

A histogram can be represented in different ways. Some of them are given below with the histogram example as well.

## Types Of Histograms

 A normal distribution: In a normal distribution, points on both sides of the average are alike. A bimodal distribution: In a bimodal distribution, the data are separately analyzed as a normal distribution. Therefore they are represented as two different peaks. A right-skewed distribution: A right-skewed distribution, also known as positively skewed distribution, is where a large number of data values occur on the left side whereas a fewer number of data values occur on the right side. A right-skewed distribution occurs when the data on the left-hand side of the histogram has a low range boundary, for example, 0. A left-skewed distribution: A left-skewed distribution which is also known as negatively skewed distribution. In a left-skewed distribution, a large number of data values appear on the right side whereas a fewer number of data values occur on the left side. A right-skewed distribution occurs when the data has a low range boundary on the right-hand side of the histogram, for example, 100. A random distribution: There is no pattern in a random distribution histogram and thus has several peaks. The reason behind this could be that the data properties were combined.

The table above will not only teach you the different types of histograms but also how to draw a histogram.

1. What are the applications of a histogram in real life?

A histogram can be used in numerous places and situations in real life. The most frequently used fields are:

1. In Stock exchange: A histogram is used to identify the trade at different places or different groups of investors.

2. In Medical and Clinical Research: A histogram in Medical and Clinical Research is useful to identify the presence or absence of a condition among different categories of people.

3. In photography: In photography, a histogram is used for Image processing and digitization.

4. In Six Sigma: A histogram is used to study the defect pattern across different categories of samples

Therefore, a histogram as a tool of simplicity and easy work has diverse uses.

2. Who discovered histogram and why was it named ‘histogram?’

Karl Pearson was the first person to discover histogram in 1891. The term ‘histogram’ was coined using two words: “historical diagram” which is obviously the function of a histogram, that is to display past data.