If you prefer the spoken word over the written word, check out our YouTube channel, and this tutorial showing how to create a histogram in SPSS. If there is an even number of values, the midpoint between the two closest values is taken. You should now be able to create a histogram within SPSS using one of its legacy tools.
If you want to save your histogram, you can right-click on it within the output viewer, and choose to copy it to an image file (which you can then use within other programs). You’ll notice that SPSS also provides values for mean and standard deviation. The y-axis (on the left) represents a frequency count, and the x-axis (across the bottom), the value of the variable (in this case Height). This video explains the step by step construction method of histogram when mid points of class intervals are given with the help of an example.To view more E. The SPSS output viewer will pop up with the histogram that you’ve created. You’re now ready to create the histogram. We suggest you also tick the Display normal curve option, though this is optional. You can do this by selecting the variable, and then clicking the arrow (as above). You need to select the variable on the left hand side that you want to plot as a histogram, in this case Height, and then shift it into the Variable box on the right. The simplest and quickest way to generate a histogram in SPSS is to choose Graphs -> Legacy Dialogs -> Histogram, as below. For example, are there more heights at the top end than at the bottom end – in other words, is the distribution skewed? A histogram will go some way to answering this question. We want to know how the frequency of heights is distributed. The variable we’re interested in out of the three you can see here is height.
Then use the boundaries that best reveal these persistent properties.
When using a calculator or software to plot histograms, experiment with different choices for boundaries, subject to the above restrictions, to find out which graphical properties (modality, skewness or symmetry, outliers, etc.) persist and which are just spurious effects of a particular choice of boundaries. The purpose of these graphs is to "see" the distribution of the data.
One can, of course, similarly construct relative frequency and cumulative frequency histograms. $$\textrm\\\hlineĤ - 5 & 3.5 - 5.5 & 6 & 1/5 & 10 \\\hlineĦ - 7 & 5.5 - 7.5 & 12 & 2/5 & 22\\\hlineĨ - 9 & 7.5 - 9.5 & 4 & 2/15 & 26\\\hlineġ0 - 11 & 9.5 - 11.5 & 3 & 1/10 & 29\\\hlineĪ frequency histogram is a graphical version of a frequency distribution where the width and position of rectangles are used to indicate the various classes, with the heights of those rectangles indicating the frequency with which data fell into the associated class, as the example below suggests.įrequency histograms should be labeled with either class boundaries (as shown below) or with class midpoints (in the middle of each rectangle). The smallest and largest observations in each class are called class limits, while class boundaries are individual values chosen to separate classes (often being the midpoints between upper and lower class limits of adjacent classes).įor example, the table below gives a frequency distribution for the following data: Data values are grouped into classes of equal widths. A frequency distribution is often used to group quantitative data.