Answer :
Final answer:
Relative frequency is calculated by dividing the frequency of a class by the total number of data points. Cumulative frequency and cumulative relative frequency provide an aggregated count up to a certain data point and its respective proportion.
Explanation:
The concept of relative frequency helps in understanding how often certain results occur in comparison to the total number of outcomes. In a dataset, the relative frequency of each class is calculated by dividing the frequency of that class by the total number of data points. To illustrate this concept, consider a situation where a class has a frequency of 3 out of a total of 100 data points. The relative frequency would then be 3/100 or 0.03. Cumulative frequency and cumulative relative frequency are other important concepts which describe the aggregate frequency up to a certain point in the dataset and the corresponding proportion.
For example, if you have a cumulative relative frequency of 0.28 and a dataset of 50 values, it implies that 28% of the data are below the threshold. This percentage indicates that 14 values (since 28% of 50 is 14) are less than the value at the 28th percentile. If the data values include multiple occurrences of numbers like 4, 5, and 6, and the 14th value is a 6, then the 28th percentile lies between the last six and the first seven, giving us a 28th percentile of 6.5.
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