Final answer:
The question involves matching statistical terms such as frequency table, absolute frequency, relative frequency, cumulative frequency, and frequency distribution with their appropriate definitions, designed to help students understand how to organize and analyze data.
Step-by-step explanation:
When working with statistical data, it is often useful to know how many times a certain value appears. This count is known as frequency, and a frequency table is a tool used to organize data values along with their frequencies. To calculate the relative frequency of a data value, you divide the frequency by the total number of data values in the data set. Meanwhile, the cumulative relative frequency is obtained by adding the relative frequencies of all the data values that precede the current value in the table, including the current value's relative frequency.
Cumulative relative frequencies provide insight into the proportion of data points that fall below a certain value, helping us understand the data in a cumulative sense. For clarification, here is a list matching terms to their definitions:
- Frequency Table — A table that lists data values along with their frequencies, which can be tallies, counts, or percentages.
- Absolute Frequency — The number of times a specific data value appears in a data set.
- Relative Frequency — A percentage that represents the ratio of the absolute frequency of a value to the total number of data observations in the set.
- Cumulative Frequency — The sum of relative frequencies of all data values that come before a specific value in a frequency distribution, including the relative frequency of the current data value.
- Frequency Distribution — A grouping of data values or intervals used to categorize and separate observations in the data set.
Understanding these concepts allows for better analysis and visualization of data through techniques such as histograms and frequency polygons, which graph frequency distributions.