Ungrouped Data: When a data collection is vast, a frequency distribution table is frequently used to arrange the data. A frequency distribution table provides the...
Ungrouped Data: Know Formulas, Definition, & Applications
December 11, 2024A chart that shows frequencies for intervals of values of a metric variable is known as a Histogram. This is a form of representation like a bar graph, but it is used for uninterrupted class intervals. Also, it shows the underlying frequency distribution of a set of continuous data.
This allows the examination of the data for its underlying distribution, irregularity, distortion, etc. The group of data is called classes and in the condition of a histogram, they are known as bins because we can think of them as containers that accumulate data and fill up at a rate equal to the frequency of that data class.
A histogram is a graphical representation that arranges a group of data into user-specified ranges. Similar to a bar graph, the histogram converts a data series into an easily interpreted visual by taking many data points and grouping them into logical ranges or bins.
The classification of histograms can be made based on the frequency distribution of the data. There are four different types of the histogram, they are:
A uniform-shaped histogram indicates very compatible data. The frequency of each class is very related to that of the others. A data set with a uniform-shaped histogram may be multimodal – having multiple intervals with the maximum frequency. One manifestation of a uniform distribution is that the data may not be split into separate intervals or classes. Another prospect is that the scale of the histogram may need to be adjusted to offer meaningful observations.
Example:
A histogram with a leading ‘mound’ in the centre and related tapering to the left and right. One manifestation of this shape is that the data is unimodal – meaning that the data has a single mode, recognized by the ‘peak’ of the curve. If the shape is symmetrical, then the mean, median, and mode are all unique values. Note that a normally allocated data set creates a symmetric histogram that looks like a bell, leading to the common term for a normal distribution, a bell curve.
Example:
This shape is not particularly defined, but we can note nevertheless that it is bi-modal, having two separated classes or intervals equally representing the maximum frequency of the distribution.
Example:
A probability histogram is a graph that constitutes the probability of each outcome on the \(y\)-axis and the possible outcomes on the \(x\)-axis. It is a graphical portrayal of the probability distribution. They are the idealized depiction of the results of a probability experiment. It has a wide range of implementation in statistics.
Example:
Histograms are commonly used in statistics to demonstrate how many of a certain type of floater occur within a specific range. For example, a census concentrated on the demography of a country may use a histogram to show how many people are between the ages of \(0-5, 6-10, 11-15, 16-20, 21-25\), etc.
Histograms can be specially made in several ways by the analyst. The first is to change the interval between bins.
The other thought is how to define the \(y\)-axis. The most basic label is to use the frequency of circumstances observed in the data, but one could also use a percentage of total or density instead.
Here we have provided the difference between Histogram and Bar Graph:
Q.1. A teacher wanted to analyze the performance of two sections of students in a mathematics test of \(100\) marks. Looking at their performances, she found that a few students got under \(20\) marks and a few got \(70\) marks or above. So she decided to group them into intervals of varying sizes as follows: \(0-20, 20-30, ….. 60-70, 70-100\). Then she formed the following table:
Marks | Number of Students |
\(0-20\) | \(7\) |
\(20-30\) | \(10\) |
\(30-40\) | \(10\) |
\(40-50\) | \(20\) |
\(50-60\) | \(20\) |
\(60-70\) | \(15\) |
\(70\)-above | \(8\) |
Total | \(90\) |
Ans: We need to make certain changes in the lengths of the rectangles so that the areas are again proportional to the frequencies.
The steps to be followed are given below:
When the class size is \(20\), the length of the rectangle is \(7\). So, when the class size is \(10\), the length of the rectangle will be \(\frac{7}{{20}} \times 10 = 3.5\)
Therefore, the modified table will be as follows.
Marks | Frequency | Width of the class | Length of the rectangle |
\(0-20\) | \(7\) | \(20\) | \(\frac{7}{{20}} \times 10 = 3.5\) |
\(20-30\) | \(10\) | \(10\) | \(\frac{10}{{10}} \times 10 = 10\) |
\(30-40\) | \(10\) | \(10\) | \(\frac{10}{{10}} \times 10 = 10\) |
\(40-50\) | \(20\) | \(10\) | \(\frac{20}{{10}} \times 10 = 20\) |
\(50-60\) | \(20\) | \(10\) | \(\frac{20}{{10}} \times 10 = 20\) |
\(60-70\) | \(15\) | \(10\) | \(\frac{15}{{10}} \times 10 = 15\) |
\(70-100\) | \(8\) | \(30\) | \(\frac{8}{{30}} \times 10 = 2.67\) |
Since we have calculated these lengths for an interval of \(10\) marks in each case, we may call these lengths as “proportion of students per \(10\) marks interval”.
So, the correct histogram with varying width is given in the below figure.
Q.2. Given below is a histogram.
How many employees are getting the highest salary?
Ans: From the given data,
The class interval \(25000-30000\) describes the highest salary in rupees.
The bar graph is drawn between \(25000-30000\) gives the number of employees with the highest salary.
The height of a bar graph drawn between the salary range of \(25000-30000\) is \(4\). Hence, there are \(4\) employees who are getting the highest salary.
Q.3. The following table gives the lifetimes of \(400\) LED lamps. Draw the histogram for the below data.
Lifetime | Number of lamps |
\(300-400\) | \(14\) |
\(400-500\) | \(56\) |
\(500-600\) | \(60\) |
\(600-700\) | \(86\) |
\(700-800\) | \(74\) |
\(800-900\) | \(62\) |
\(900-1000\) | \(48\) |
Ans: The histogram for the given data is shown below:
Q.4. The marks obtained by \(40\) students in an examination are given below.
\(27, 18, 15, 21, 48, 25, 49, 29, 27, 21,\)
\(19, 45, 14, 34, 37, 34, 23, 45, 24, 42,\)
\(8, 47, 22, 31, 17, 13, 38, 26, 3, 34,\)
\(29, 11, 22, 7, 15, 24, 38, 31, 21, 35\)
Draw a histogram representing data.
Ans: The given data can be tabulated as
Class Interval | Number of students |
\(0-10\) | \(3\) |
\(10-20\) | \(8\) |
\(20-30\) | \(14\) |
\(30-40\) | \(9\) |
\(40-50\) | \(6\) |
Total: \(40\) |
The histogram showing the given data is below:
Q.5. Given below is a histogram.
How many employees are getting the lowest salary?
Ans: From the given data,
The class interval \(0-5000\) describes the highest salary in rupees.
The bar graph drawn between \(0-5000\) gives the number of employees with the lowest salary.
The lowest of a bar graph drawn between the salary range of \(0-5000\) is \(12\). Hence,\(12\) employees are getting the highest salary.
In this article, we learned about the definition of histogram charts, types of histograms, and their meaning. We also saw the difference between bar graph and histogram and solved examples on a histogram.
Q.1. What is a histogram?
Ans: A chart that shows frequencies for intervals of values of a metric variable is known as a histogram.
Q.2: What is a histogram used for?
Ans: A histogram is a graph that is used to show frequency distributions.
Q.3. What is a histogram? Discuss with example.
Ans: A histogram is a graphical representation that arranges a group of data into user-specified ranges. Similar to a bar graph, the histogram liquifies a data series into an easily interpreted visual by taking many data points and grouping them into logical ranges or bins.
Q.4. What is a histogram vs bar graph?
Ans:
Q.5. How do you describe a histogram graph?
Ans: We describe a histogram graph based on the shape. There are three shapes of a histogram graph.
Learn All the Concepts on Bar Graphs
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