We could also decrease the bin width to 10,000:
Notice how this increases the width of each bin and reduces the total number of bins.
We can change this to any number we’d like.įor example, we could increase the bin width to 50,000: In the window that appears to the right, we can see that Excel chose the bin width to be 29,000. To adjust the bin width, right click the horizontal axis on the histogram and then click Format Axis from the dropdown: This creates the following histogram by default: Then we’ll click the INSERT tab along the top ribbon, then we’ll click the Histogram icon within the Charts section. Next, we’ll highlight the two columns of data: Step 1: Create the Dataįirst, we’ll create the following dataset that shows the annual income of 26 different people: This tutorial provides a step-by-step example of how to create a histogram in Excel and how to modify the bin width so that the histogram looks exactly how you’d like. Postscript: Thanks to John Peltier for innumerable charting inspirations over the years.A histogram is a plot that can be used to quickly visualize the distribution of values in a dataset. Lastly, you can remove the tick marks and labels on the secondary axes to clean up the look. Format the X-Y series appearance to taste (I suggest removing value markers).Change the secondary Y-axis range to 0-1.This will effectively align the primary and secondary X-axes. Change the secondary X-axis range to 0.5-5.5 (i.e., 0.5 on either side of the column chart category values).Change the series to use the secondary axes (both X and Y).This might require some editing of the chart series to force a single series to use your desired X and Y values. This will be the number of data points in the normal distribution curve.į2 =NORMDIST(E2,$B$9,$B$14,FALSE) etc. StDev =SQRT(B13/(B12-1)) Part 2: Chart Trickery Data table:Ĭolumn D is just an incremental counter.
I used Excel 2007 for this hopefully you have the same options available in your version. Second, I employed some chart trickery to make the normal distribution curve look right when superimposed on the column chart. First, I reverse-engineered the grouped data to come up with an appropriate mean and standard deviation on this scale.
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