A cumulative frequency distribution is a graphical representation of the number of cases occurring within a given category. Using SPSS, you can create what is known as a histogram, which provides a visual display of this data. The category is displayed on the x-axis while the frequency is displayed on the y-axis. A visual representation of your data can be helpful in conceptualising abstract numbers.

- Skill level:
- Moderate

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## Instructions

- 1
Enter your data into SPSS under the "data view" page. Make sure that you have named all your variables in the "variable view page."

- 2
Click the "analyse" tab at the top of the screen. From the drop-down menu, select "descriptive statistics" and then "frequencies."

- 3
Highlight all the variables you would like included in the cumulative frequency distribution and individually move them over to the "variables" column. Make sure you have the "display frequency tables" box checked in the bottom left of the pop-up. Once you have selected all your variables, click the "statistics" button.

- 4
Check all the appropriate boxes you would like to be included in your analysis. Cumulative frequency distributions often include a mean, median and mode. You may also like to view the standard deviation, variance and range of your data. Click the "continue" button.

- 5
Click the "charts" button. Under chart type, select "histogram." Select "frequencies" under chart values. Click "continue."

- 6
Click the "OK" button. SPSS will produce an output displaying your data. The histogram displays your cumulative frequency distribution and the statistics box shows all the other analyses, such as standard deviation, standard error and anything else you chose in Step 4.

#### Tips and warnings

- Make sure that you have named your variables in a recognisable manner. If you have a large data set, it is easy to forget which names refer to certain variables.
- If you are using nominal or ordinal data, you can use a cumulative frequency distribution to look at exact numbers within each category. If you are using ratio or interval data, you may need to examine how your data fits into a range of numbers.