## Setting up the Data

Setting up the data for an Excel histogram is a straightforward process. First, you need to select the data you want to be displayed in the histogram. You will then need to **organize the data into a chart**, arranging the data into numerical order from the *lowest value to the highest*. There should *not be any blank cells* in your data selection. Once the data is in order, you can move on to the next step.

### Select the data you want to visualize

**Creating a histogram in Microsoft Excel** is a great way to easily visualize your data so you can draw clear conclusions from the information.

To do this, first ensure that your Excel document contains the data you want to visualize. You’ll need two columns of data – one containing the range of values that appear in your data set and the other containing the *frequency* of each value within that set, or how many times it appears. The frequency should be listed in adjacent cells to enable easy selection when creating the histogram.

Next, determine which range of numbers you want to appear on your **x-axis** (horizontal axis). This will represent your *bins* – or intervals – into which the frequencies will be grouped before graphing. Once you’ve chosen a range (e.g., 0-10), make sure all values included on it are present in both columns so they appear correctly on the x-axis after graphing.

Once you’ve selected and organized your data, you’re ready to create a histogram! Microsoft Excel offers an intuitive and user-friendly tool for plotting charts like these based on selections from worksheets within them same file. All that’s left is to select what type of graph you’d like to create and adjust its settings for maximum clarity and accuracy!

### Create a frequency table

When creating an Excel histogram, the first step is to create a frequency table. A frequency table allows us to easily highlight the amount of times a certain value or item appears in our data set.

To do this, we will want to **sort our data from smallest to largest**, or from A-Z if you’re dealing with strings. Next, we will want to count the values within our dataset and enter them into their own column that’s titled *“Frequency”*. To find the Frequency of each item in the dataset, simply click on a cell just below your last selection and type *“=COUNTIF (‘[Range]’,‘[Value]’)”* replacing the range and value words with those applicable to your data set. This will return how many time that one value appears in your set.

After this is completed for each item, click on each cell containing a number under Frequency and copy and paste it into its own column as shown below.

Once this is completed all we need to do is format our frequency data to use it in making a histogram!

## Creating the Histogram

**Creating a histogram in Excel** is a useful way to visualize your data. It’s a great tool for understanding the distribution of data, as well as identifying any outliers or trends.

In this section, we’ll look at the steps for creating a histogram in Excel. We’ll go over the data selection, formatting, and layout that you need to **create a successful histogram**:

- Data selection
- Formatting
- Layout

### Open the histogram chart wizard

The **histogram chart wizard** is part of the Analysis tool pack in Microsoft Excel. To launch it, start by selecting a range of cells with graphing data that you want to use to form the histogram. Be sure that you have taken any steps necessary to prepare your data for analysis, such as *deleting unnecessary or empty rows and columns*.

After the cells are selected, click on the Chart Wizard icon or go to the Insert menu and choose Histogram. You should see a pop-up window asking you about your data, including which spreadsheet elements should be used for graphing. Select as many parameters as needed for accuracy and click Next.

Next, Excel will ask you about the type of graph you want for your histogram and how many bins or buckets should be used for categorizing it into ranges. You may also select automatic bin settings or create a custom binning option by clicking on *“bins”* on the left side of this screen. Click Next again when finished and choose the chart type you’d like to display (bar, line graph etc.), then click *“Finish”*. The resulting chart should appear in its own window so that you can analyze it more closely.

### Select the data range

Once you’ve gathered your data and opened Excel, select the **Data Analysis tool** from the Analysis group on the ribbon. If this is not visible, click on Insert and then on Data Analysis.

Choose **Histogram** in the list of available tools, then select the data range in your spreadsheet which contains the data you want to use to create a histogram. You can do this by selecting all columns of data, or entering a cells range if appropriate.

You can also create a histogram from **multiple series of data** by clicking on the *Multiple Histograms* option in Data Analysis. Selecting this option will bring up additional dialog boxes for entering more information about the series of data for each of which you wish to generate a separate histogram. If you have chosen this option, follow all remaining steps as normal but with each series individually until specified otherwise.

### Select the bin range

**Bin range** is the range of values used to group data into bins or intervals for the purposes of creating a histogram. Generally, it is best to set the bin interval range to be within the range of data. Excel will usually calculate and adjust the intervals dynamically if auto bins option is selected.

To create a histogram, select the **“Data”** tab then click on **“Data Analysis”** found in the **“Analysis”** group. Select **Histogram** from the list and click **OK**. Excel will then launch a wizard to set up your histogram chart.

The first page of the wizard includes options for setting up source data, bins and output options. The dialog box to select bin range will open where users can enter numerical values for bin ranges or specify manual ranges like **10-20, 21-30** etc.. Click **OK** once done and follow through with other steps in order to create your histogram in Excel.

## Customizing the Histogram

**Histograms** are an excellent way to visualize and interpret your data, and *Microsoft Excel* makes it easy to create one quickly and customize it to meet your specific needs. There are various ways to customize your Excel histogram, including:

- Setting the bin size
- Changing the color palette
- Adding titles and labels

Let’s take a closer look at how to customize your Excel histogram.

### Change the chart type

Once all your data is entered and refined, you can begin customizing the histogram. Changing the chart type of an existing histogram to one of the other chart types can help better visualize kurtosis and skewness. To do this:

- Select your histogram data, go to Insert tab on the ribbon and choose one of the other chart types from the Charts Group.
- Right-click your chart and select
**Change Chart Type**, located in the dropdown menu.

Once in the Change Chart Type dialog box, you will see several options for changing your histogram into a different chart type (such as column, line, area or bar). Select whichever one fits best with your purpose for making a histogram (looking at kurtosis or skewness). For example, if you have a lot of categories or bins in your data set and want to compare them easily opt for a Line or Area type chart instead of a traditional Histogram.

Additionally, within some charts (such as column) is an option that appears in **“Chart subtypes”** labeled **“Clustered”**; if enabled it will plot two measures within each bin side-by-side rather than overlapping allowing you to create more accurate measurements across different series (e.g. comparing sales between products within specific year quarters). Changing this subtype allows you further refine how Excel visualizes numerical data points which can lead to more accurate interpretations of kurtosis or skewness when compared back-to-back with traditional Histograms.

### Edit the axis labels

When creating an Excel histogram, it is important to give each axis an appropriate label to help anyone looking at the graph more easily understand what it represents. To do this, double click on the horizontal or vertical axis. This will bring up the **Format Axis Menu**. Here, you can customize the text for both the **Horizontal** and **Vertical** axes labels as well as customize their font size and color.

If you are graphing a Measurement over Time, be sure to use *Year or Date* as your **X-Axis label** and include units of measurements when labeling your **Y-Axis** such as *grams/mL*. Keeping these labels consistent with any other graphs you are presenting will ensure a clear understanding of your data points.

### Adjust the bin width

Having a *Histogram* in Excel provides valuable insight into the data you have entered. Data can be represented graphically, allowing you to interpret it more quickly. To make your Histogram more meaningful and accurate, it is important to consider the **width of the bins**. The width of each bin represents a range of data that includes all values within that range.

For example, if your data is comprised of **10% between 0 and 5, 15% between 5 and 10, 20% between 10 and 20, 30% between 20 and 30, 25% between 30 and 40**; these five ranges can be categorized as five bins with a width of 5 from 0-5, 5-10 etc. The choices for setting the width of your bin will depend on how precise you need the Histogram to be.

When customizing a Histogram in Microsoft Excel, click on “*Stacked Column*” at the top to open up a dialog box for changing the bin width settings. In this settings window, you can change “**Bin Size**” by manually entering any whole number value or by selecting one available value from its dropdown list. Additionally in this window there is also options present for choosing whether or not gap options should be selected while making histogram or not. To complete this configuration process click ‘Ok’ button which ultimately updates your histogram according to selected setting parameters.

## Analyzing the Histogram

**After you’ve created your Excel histogram**, it’s time to analyze it to get an understanding of the results. Histograms are used to assess the distribution of data and identify any trends. You can also use histograms to *compare two different sets of data*. With the help of this data visualization tool, you can track and compare data over time.

Let’s look at how to **analyze a histogram**:

### Interpret the shape of the histogram

The shape of a histogram can help you to determine the distribution of your data. If the shape of a histogram is **skewed to the right**, this indicates that there are more *large values in the data* than small values. Conversely, if it is **skewed to the left**, this suggests that there are more *small values than large*. A **symmetrical histogram** suggests that the values are *evenly distributed between large and small*.

There may also be **multiple peaks or dips** in the shape of your data or various **clusters** which indicate a variety of separate distributions.

In addition to interpreting its shape, you can also identify whether your data follows a **normal distribution** by looking at its histogram. A normal distribution is one which has *exactly one peak and no skewness (symmetrical)*. If all of your data points form a symmetrical bell-like curve around one point, then it is likely following a normal distribution. To check if data follows a normal distribution, you can use various statistical tests such as *Q-Q plots or ShapiroWilk tests*.

### Identify the outliers

**Outliers** are observations that are far away from the normal observations in a data set. It is important to identify these potentially influential outliers, which can often have a very *large effect on the results of an analysis or experiment.*

When assessing a histogram, it is helpful to compare the distribution and shape with others similar to it, such as if you are comparing two different brewing methods for coffee. When looking at the histogram, you should observe whether there is an outlier present amongst groupings of the binned data. **Binning data** involves breaking down large datasets into smaller groups by categorizing them into more manageable segments called bins or buckets.

Checking if any values appear to be outside of the distributions in comparison to other binned buckets (which form an overall shape) can help identify any outliers that may indicate an incorrect answer or sample variation. Outliers typically stand out and stand apart from normal groups in a graph or display, *drawing attention*. For instance, if one observed bucket had no values and all others had some results indicated within their grouping that could point to an outlier.

Understandably identifying outliers can differ depending on context; however, it is always necessary for reliability and rigor when analyzing your data to make sure you have identified any outliers present in your collected data set prior to making any inferences about trends or patterns.

### Calculate the median and mode

When you have plotted your data into a histogram, you can use the histogram to calculate the **median** and **mode** of the data. The *median* is the middle value in the distribution, and is equal to the number of items below it plus one half of the number of items above it. To determine the median from a histogram, find where the greatest number of points are represented and then move downward keeping track of how many points are beneath each bar until you reach **50%**. The bar at that point is equal to your median.

The *mode* is represents in a histogram as which bar contains has most points plotted underneath it. For example, if there are three bars with **5, 6 and 8 points** respectively, then 8 would represent the mode because that was most occurrences of any one point on the graph.