If you plot the data you will notice a very short normal distribution curve, barely visible as a bell curve due to differences in scale. The first parameter is the values we calculated, the second the mean, the third the standard deviation and the last should be FALSE as we don’t want cumulative (NORMDIST(Q1,100.84,27.49,FALSE)). Now for each of those points the normal distribution shall be calculated using Excel’s NORMDIST function. Starting at minus 3 standard deviations (equal to the mean minus 3 standard deviations (18.36)) increment the value by 1.6496 all the way up to positive 3 standard deviations(183.32). Multiply the standard deviation (27.49) by 6 to get 164.96, divide by 100 to get an increment of 1.6496. 100 points will be created for a nice smooth curve.
The bell curve looks nice when it covers the full 6 standard deviations. Increase the Line Style Width so that it starts looking like a histogram with no gaps.įor the normal curve the points need to be created first. This will produce a scatter chart with the following error bars. Select Display Direction Minus, End Style No Cap and Error Amount Percentage 100%.
Select the chart and click on the ribbon menu, Layout, then Error Bars and then More Error Bars Options. Select the data and produce a scatter chart with smooth lines. Overlaying a normal curve is a little trickier, firstly, the above column chart can’t be used and the histogram must be produced using a scatter chart. Using a column chart a histogram can be produced. The FREQUENCY Function must be entered as an array (ctrl-enter). Set up the bins starting at the minimum and ending at the maximum, using the Excel FREQUENCY function to determine frequency in each bin. To get a bin width, divide the range (156) by the number of bins (9) which results in 17.33, round this up to an even 20 to produce nice round bin widths. Using Sturges’ formula the number of bins is 9, using the square root method the number of bins is 15. Start by calculating the minimum (28) and maximum (184) and then the range (156). This is done by creating bins of a certain width and counting the frequency of the samples that fall in each bin. The first thing to do is produce the histogram. The samples can be checked to confirm normally distributed by comparing the mean, median and mode which should all be equal.
The actual mean and standard deviation was 100.84 and 27.49 respectively. I created samples with a mean of 100 and standard deviation of 25, function RandNormalDist(100, 0.25). To produce my random normal samples I used VBA function RandNormalDist by Mike Alexander.
You can find more Excel tutorials on this page.This tutorial will walk you through plotting a histogram with Excel and then overlaying normal distribution bell-curve and showing average and standard-deviation lines.
This decreases the width of each bin and increases the total number of bins in the histogram.įeel free to modify the bin width to any value you’d like and keep in mind the following rules of thumb: 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. A histogram is a plot that can be used to quickly visualize the distribution of values in a dataset.