When to use a histogram or bar graph?

A histogram should be used when the data is continuous, and a bar graph should be used when the data is discrete.Continuous data is numerical data that can be measured. So, if you're comparing the temperature of the water in a lake in different months, then you use a histogram. If you're counting the number of boaters on the lake in a given month, then you use a bar graph.

What are the advantages and disadvantages of a bar graph?

The advantages of a bar graph are that they are easy to understand, easy to create, and commonly used. This means that they can be easily put together, and your audience won't struggle with interpreting them.The disadvantages of a bar graph are that they do require some additional explanation to fully understand, they're easy to manipulate to show false or misleading results, and they can't show patterns or how the data affect one another.This means that bar graphs have to be viewed with a critical eye unless you know the person who made them and their agenda.In short, a bar graph's simplicity is both its greatest asset and an exploitable flaw.

What are the advantages and disadvantages of a histogram?

The advantages of a histogram are that it is a simple and versatile graph that is easy to put together, as well as being easy to read and interpret. Histograms can be used in many different situations to get the point across, and everyone's familiarity with bar charts, in general, makes them easy to read and work with.The disadvantages of a histogram are that they are extremely focused on the number of 'bins,' or lines, and are heavily affected by the maximum and minimum of the variable.Altering the max and min can alter the look of a graph dramatically, which can be misleading. Also, their simplicity does make it difficult to see the effects and distribution of the data.

Histogram Vs. Bar Graph: What’s The Difference?

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Both histograms and bar graphs are used to display data visually. Not only that, but both visual representations use a series of bars to convey the information, making it difficult to tell which is which.

Most people are familiar with a bar graph, but histograms are less common. That being said, it’s entirely possible that you’ve seen a histogram before without realizing what one was. And due to them being less common, it’s very easy to mistake one for a bar graph.

The main way to tell the difference between a histogram and a bar graph is how they’re put together. Because bar graphs are used for discrete data, the bars don’t touch one another and are separate pieces of data. With a histogram, the bars do touch one another, and the data aren’t separate due to the fact that they’re used to represent continuous data.

Key Takeaways:

Histogram	Bar Graph
A histogram is used to represent continuous data.	A bar graph is used to represent discrete data.
Histograms are used to show averages. As the data’s in a range, putting them into a histogram makes it easy to see which values come up most often.	Bar graphs are used for comparison purposes. Putting data into bar graph form makes it easy to see which value is larger and by how much.
In a histogram, the bars on the chart touch one another.	In a bar graph, the bars on the chart have a gap between them.
The ordering of the bars in a histogram is important, as it’s part of how you interpret the data.	With a bar graph, the bars can be ordered in any way you wish. Traditionally it’s from high to low, but that’s just convention.

What Is a Histogram?

A histogram is a type of bar chart that is used to represent continuous data. For those unfamiliar with types of data, continuous data is a type of numerical data that has a range.

Generally speaking, continuous data is a value that can be measured, such as temperature, height, or age. The reason that it has a range is that any measurement can be pushed to an ever more precise value.

Due to this, histograms are in many ways fixed. The order in which the bars are placed is important, as it follows a range. For instance, if you wanted to plot the height of apple trees in an orchard, you would use a range. Each tree is going to be a different height, but you can round them to feet or inches and then place each value into a histogram.

Unlike a bar graph, which compares different values, a histogram is constructed to compare frequency. As with the apple tree example, you would therefore see how likely the trees are to be at certain heights. The layout of the histogram would show you the average height of the trees in the orchard, as those bars would be the highest.

What Is a Bar Graph?

A bar graph is a type of bar chart that is used to represent and compare discrete data. Discrete data is in many ways the opposite of continuous data. It doesn’t exist in a range and is limited to a certain set of values.

For instance, if you’re comparing how many pets each student has in their household, it’s not possible to have a range – you can’t get more precise than two pets, as it’s impossible to have a fractional pet.

Bar graphs, therefore, can be arranged in any way the creator likes. The traditional way is to have it go from highest to lowest, or possibly lowest to highest, but the order in which the bars are placed is unimportant in terms of the data. Also, as the data isn’t tied together, the bars on a bar graph have a noticeable gap between them.

A bar graph is used to compare discrete data, such as what type of pet people in a class own. You can therefore represent the most popular type of pet in the sample.

Tips for When to Use Histogram

Histograms are useful tools in the right circumstance. Here’s when you should consider using one.

Histograms represent continuous data, which is something that can be measured. So if your data deals with time, length, weight, or temperature, then a histogram is likely what you want.
Histograms are used to show averages and ranges. If your data has a range and you want to easily show where the biggest grouping is, histograms are likely the way to go.

Tips for when to use a Bar Graph

Bar graphs are a very common type of chart. They are easy to make and easy to understand, which makes them popular.

Bar graphs are used for discrete data, which is something that can be counted. If you’re counting the number of cars in a lot that is blue, green, or red and comparing those numbers, then a bar graph is a good choice.
Bar graphs are used for comparison purposes. They show how different countable values compare to one another. Such as how many people have dogs rather than cats.

Histogram vs. Bar Graph FAQ

When to use a histogram or bar graph?

A histogram should be used when the data is continuous, and a bar graph should be used when the data is discrete.

Continuous data is numerical data that can be measured. So, if you’re comparing the temperature of the water in a lake in different months, then you use a histogram. If you’re counting the number of boaters on the lake in a given month, then you use a bar graph.
What are the advantages and disadvantages of a bar graph?

The advantages of a bar graph are that they are easy to understand, easy to create, and commonly used. This means that they can be easily put together, and your audience won’t struggle with interpreting them.

The disadvantages of a bar graph are that they do require some additional explanation to fully understand, they’re easy to manipulate to show false or misleading results, and they can’t show patterns or how the data affect one another.

This means that bar graphs have to be viewed with a critical eye unless you know the person who made them and their agenda.

In short, a bar graph’s simplicity is both its greatest asset and an exploitable flaw.
What are the advantages and disadvantages of a histogram?

The advantages of a histogram are that it is a simple and versatile graph that is easy to put together, as well as being easy to read and interpret. Histograms can be used in many different situations to get the point across, and everyone’s familiarity with bar charts, in general, makes them easy to read and work with.

The disadvantages of a histogram are that they are extremely focused on the number of “bins,” or lines, and are heavily affected by the maximum and minimum of the variable.

Altering the max and min can alter the look of a graph dramatically, which can be misleading. Also, their simplicity does make it difficult to see the effects and distribution of the data.

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Author

Di Doherty

Di has been a writer for more than half her life. Most of her writing so far has been fiction, and she’s gotten short stories published in online magazines Kzine and Silver Blade, as well as a flash fiction piece in the Bookends review. Di graduated from Mary Baldwin College (now University) with a degree in Psychology and Sociology.

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