By definition, the sum must be unity.
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You will need endpoints of your range (for example age: 12-14, 15-17. The endpoints are 14 and 17). You will also need the cumulative total of the relative frequencies (add all relative frequencies). -To find the relative frequency = value over total (ex, age 12-14, 51 have diabetes, 90 do not. The total of those having diabetes is 3800. So for the relative frequency of ages 12-14, it is 51/3800=0.01342. Do this for all ranges). -To find the Cumulative Frequency: add all these frequencies (separate for "yes" diabetes and "no" diabetes). Use endpoints of your range for the x-axis (horizontal axis). Then use the cumulative frequencies as your y-axis (vertical axis).
It is always 100%.
The sum of the relative frequencies must equal 1 (or 100%), because each individual relative frequency is a fraction of the total frequency. The relative frequency of any category is the proportion or percentage of the data values that fall in that category. Relative frequency = relative in category/ total frequency It means a number in that class appeared 20% of the total appearances of all classes
According to Anderson, Sweeney Williams book Essential of Statistics For Business and Economics, 4e Edition, 2006 p. 34 cumulative frequency distribution is "a variation of the frequency distribution that provides another tabular summary of quantitative data." In simple terms, the cumulative frequency distribution is the sum of the frequencies of all points or outcomes below and including the current point.
A discrete distribution is one in which the random variable can take only a limited number of values. A cumulative distribution, which can be discrete of continuous, is the sum (if discrete) or integral (if continuous) of the probabilities of all events for which the random variable is less than or equal to the given value.